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Category Archives: Cybersecurity

Trump’s Retaliation Against Chris Krebs — and the Cybersecurity Industry’s Deafening Silence

Chris Krebs, the former director of the Cybersecurity and Infrastructure Security Agency (CISA), was fired by Donald Trump in 2020 for publicly affirming that the presidential election was secure and free from widespread fraud. Fast-forward to April 2025: Trump, now back in the White House, issued an executive order revoking Krebs’ security clearances and ordering a federal investigation into his conduct, specifically targeting both Krebs and his employer, SentinelOne. The order also suspended clearances for other SentinelOne employees and threatened the company’s ability to do business with the government.

Krebs responded by resigning from SentinelOne to fight the administration’s campaign against him, stating, “This is a fight for democracy, freedom of expression, and the rule of law. I’m ready to give it my all”. SentinelOne’s stock dropped, and the chilling effect on the broader cybersecurity sector was immediate and palpable.

The Industry’s Response: Silence, Not Solidarity

Despite Krebs’ reputation for professionalism and integrity, the cybersecurity industry has, with rare exceptions, responded with silence. Reuters reached out to 33 major cybersecurity firms and three industry groups—only one responded with a comment. Industry leaders, major vendors, and conference organizers have largely avoided public statements. Even companies with direct ties to Krebs, such as Microsoft and CrowdStrike, declined to comment.

This silence is not just disappointing—it’s dangerous. The executive order against Krebs is not merely a personal vendetta; it is a test of constitutional norms and the independence of the cybersecurity profession. By targeting Krebs for telling the truth, the administration is sending a message: dissent—especially when it contradicts the preferred political narrative—will be punished. The industry’s lack of response is, in effect, complicity.

Why This Matters

  • Chilling Effect: If a high-profile, well-respected figure like Krebs can be targeted for doing his job, no one in the industry is safe. The message is clear: toe the line or risk your career and your company’s future.
  • Erosion of Trust: Cybersecurity is built on trust and integrity. If practitioners cannot speak the truth without fear of retaliation, the entire profession is undermined.
  • Precedent for Authoritarianism: The use of executive power to punish private citizens and companies for protected speech is a hallmark of authoritarianism. The industry’s silence enables further overreach.

What Every RSA Attendee Should Do

RSA Conference 2025’s theme is “Many Voices. One Community.” But a community that stays silent in the face of injustice is not united—it is complicit. Every attendee, whether you’re a practitioner, vendor, or “A-lister,” has a responsibility to meet this moment.

When you visit vendor booths or encounter cybersecurity leaders and influencers at RSA, ask them:

  • What are you and your company doing to publicly support Chris Krebs and SentinelOne?
  • How are you defending the principles of free speech and professional integrity in cybersecurity?
  • Are you willing to risk contracts, revenue, or reputation to stand up for what’s right?
  • What concrete actions will you take to ensure that truth-telling cybersecurity professionals are protected, not punished?

Don’t let them dodge. Don’t accept platitudes.

If you’re a vendor or a leader: issue a public statement. Sign an open letter. Organize a session or a panel on defending professional independence. Use your platform—on stage, on social media, in the press—to call out this abuse of power.

If you’re an attendee: demand answers. Refuse to let silence be the industry’s answer to authoritarian overreach.

Remember: Silence is not safety. Silence is capitulation. If the cybersecurity community cannot defend its own when the truth is under attack, then what exactly are we protecting?

This is your moment. Don’t waste it.

American [Cyber] Sigh

A long, long time ago
I can still remember
How those CVEs would make me smile
And I knew if I had my chance
To patch a vuln or take a stance
Maybe we’d be secure for a while

But April ides made me shiver
With each leaked memo and press release delivered
Bad news on the doorstep
Couldn’t take one more step

I can’t remember if I sighed
When I read about the program’s demise
But something broke me deep inside
The day the CVE died

So bye, bye, MITRE’s CVE pie
Checked the vuln feed in my Feely
But the Feedly ran dry
And them good old nerds were drinking whiskey and rye
Singin’, “This’ll be the day that I sigh
This’ll be the day that I sigh”

Did you write the book of flaws
And do you have faith in CISA’s cause
As the budget fails you so?
Do you believe in NVD
Can it save our infosec sanity
Now that MITRE’s left out in the cold?

Well, I know you’re chasing vulns with me
Saw your commits in the CVE tree
We both diffed those exploit clues
Man, I miss those vuln ID blues

I was a lonely analyst on the hunt
With a zero-day and a coffee cup
But I knew I was out of luck
The day the CVE died

I started singing
Bye, bye, MITRE’s CVE pie
Checked the vuln feed in my Feely
But the Feedly ran dry
And them good old nerds were drinking whiskey and rye
Singin’, “This’ll be the day that I sigh
This’ll be the day that I sigh”

Now for twenty-five years we’ve been on our own
But the funding’s gone, the seeds are sown
That’s not how it used to be
When MITRE sang for DHS
And catalogued every software mess
In a voice that came from you and me

Oh, and while the vendors looked around
The hackers stole the thorny crown
No verdict was returned
And the vuln world, it just burned
And while defenders read advisories
The attackers practiced in the dark
And we sang dirges in the park
The day the CVE died

We were singing
Bye, bye, MITRE’s CVE pie
Checked the vuln feed in my Feely
But the Feedly ran dry
And them good old nerds were drinking whiskey and rye
Singin’, “This’ll be the day that I sigh
This’ll be the day that I sigh”

Helter skelter before the summer swelter
The KEV flew off with no shelter
Zero-days high and falling fast
It landed foul on the grass
The vendors tried for a forward pass
With MITRE on the sidelines in a cast

Now the half-time air was sweet perfume
While the Red Team played a marching tune
We all got up to dance
Oh, but we never got the chance
‘Cause the vendors tried to take the field
The bug bounty band refused to yield
Do you recall what was revealed
The day the CVE died?

We started singing
Bye, bye, MITRE’s CVE pie
Checked the vuln feed in my Feely
But the Feedly ran dry
And them good old nerds were drinking whiskey and rye
Singin’, “This’ll be the day that I sigh

Oh, and there we were all in one place
A generation lost in cyberspace
With no time left to start again
So come on: Jack be nimble, Jack be quick
Jack Flash sat on a candlestick
‘Cause fire is the hacker’s only friend

Oh, and as I watched it on the stage
My hands were clenched in fists of rage
No angel born in hell
Could break that budget spell
And as the flames climbed high into the night
To light the sacrificial rite
I saw Musk laughing with delight
The day the CVE died

He was singing
Bye, bye, MITRE’s CVE pie
Checked the vuln feed in my Feely
But the Feedly ran dry
And them good old nerds were drinking whiskey and rye
Singin’, “This’ll be the day that I sigh

I met a dev who sang the blues
And I asked her for some happy news
But she just smiled and turned away
I went down to the sacred store
Where I’d checked for CVEs before
But the sysadmin said the feeds wouldn’t play

And in the streets, the hackers screamed
The CISOs cried, and the devs all dreamed
But not a word was spoken
The patching chain was broken
And the three things I admire most:
The patch, the fix, and the vuln disclosure post
They caught the last train for the coast
The day the CVE died

And they were singing
Bye, bye, MITRE’s CVE pie
Drove my vuln feed to the levee
But the levee ran dry
And them good old nerds were drinking whiskey and rye
Singin’, “This’ll be the day that I sigh
This’ll be the day that I sigh”

A Critical Analysis of ICERAID

ICERAID (iceraid[.]us) presents itself as a “GovFi protocol” that purportedly delegates intelligence gathering tasks from law enforcement to citizens. According to their materials, it rewards users with cryptocurrency tokens for capturing and uploading images of alleged “criminal illegal alien activity” and other suspected criminal behavior to their platform.

The platform claims to operate on the Solana blockchain, with users receiving ICERAID tokens for submitting photos through their app. Their marketing positions this as helping “take the strain off law enforcement” by allowing citizens to provide real-time data. The project launched a token sale that allegedly sold over 65 million ICERAID tokens, with plans for a validator staking program using Raydium LP tokens.

In February 2025, ICERAID announced a bounty program specifically targeting New York City, offering 2,000 ICERAID tokens for each photograph of “suspicious activities related to illegal immigration”. Users must connect a Solana-compatible wallet like Phantom to receive rewards after uploading images to the ICERAID Explorer.

I did some spelunking and dropped a bunch of info/artifacts on the fairly pathetic crypto scam initiative over at Codeberg.

Xitter Hit by Major Cyberattack

On March 10, 2025, Xitter experienced major service disruptions throughout the day. Users couldn’t access the platform on both mobile apps and the website. Here’s what happened and why it matters.

What Happened?

X suffered multiple waves of outages starting early Monday morning:

  • First wave: Around 6:00 AM Eastern Time, affecting about 20,000 users
  • Second wave: Around 10:00 AM ET, with over 40,000 users reporting problems
  • Third wave: Between 11:00 AM and noon, affecting nearly 30,000 users

People trying to use Xitter saw loading symbols, error messages saying “Something went wrong. Try reloading,” or couldn’t access the service at all.

Who Was Behind It?

A pro-Palestinian hacking group called Dark Storm Team claimed responsibility for the attack. They posted on their Telegram channel: “Twitter has been taken offline by Dark Storm Team,” along with screenshots showing connection failures from different global locations.

Dark Storm Team has been active since around 2023 and is known for targeting organizations in Israel, Europe, and the United States. According to security experts, the group specializes in DDoS attacks and has a pro-Palestinian orientation.

What Did Elon Musk Say?

Elon Musk, Xitter’s owner, acknowledged the attack several hours after it began: “There was (still is) a massive cyberattack against Xitter. We get attacked every day, but this was done with a lot of resources. Either a large, coordinated group and/or a country is involved.”

Later, in an interview with Fox Business, Musk made a controversial claim connecting the attack to Ukraine: “We’re not sure exactly what happened but there was a massive cyberattack to try and bring down the Xitter system with IP addresses originating in the Ukraine area.” He provided no evidence to support this claim.

What Was the Reaction?

Cybersecurity experts expressed significant skepticism about Musk’s Ukraine claim:

  • They pointed out that attack origin IP addresses can be easily masked or manipulated
  • Attackers routinely route activities through compromised systems in other countries

Ukrainian officials firmly denied any involvement. Oleksii Merezhko, chairman of Ukraine’s parliamentary Foreign Affairs Committee, stated that the Ukrainian government had “absolutely” no part in the alleged cyberattack on Xitter.

Ed Krassenstein, who claimed to have communicated with Dark Storm’s leader, contradicted Musk’s assertion. According to screenshots shared online, the group responded to the Ukraine claim by saying: “Elon Musk must provide evidence for his claim, and we will provide evidence for ours.” They allegedly threatened further attacks, warning “We can attack again. A stronger attack this time, not only on Xitter but Tesla and others.”

What Type of Attack Was It?

The incident was a distributed denial-of-service (DDoS) attack. These attacks work by:
– Overwhelming a platform’s servers with excessive traffic
– Causing slowdowns or complete outages by exhausting available resources
– Using compromised devices (forming a “botnet”) to send overwhelming amounts of data

Cybersecurity experts described this attack as “far beyond simple DoS attempts,” involving “full-scale DDoS assaults, combined with sophisticated botnet activity, credential stuffing, API abuse, and targeted application-layer attacks designed to cripple operations.”

How Did Xitter Respond?

Xitter implemented Cloudflare’s DDoS protection services to mitigate the impact. This defensive measure introduced captcha verification for suspicious IP addresses generating too many requests. By evening, the platform had largely recovered, though some users continued to experience intermittent issues.

I’m not surprised Cloudflare helps protect Nazis, but it’d be nice to live in a universe where they all crawled back under their rocks for good.

CVESky: Monitoring The Bluesky Jetstream For CVE Mentions

I mentioned this new app over at the newsletter but it deserves a mention on the legacy blog.

CVESky is a tool to explore CVE chatter on Bluesky. At work, we’re ingesting the Bluesky Jetstream and watching for CVE chatter, excluding daft bots that just regurgitate new NVD CVEs.

There are six cards for the current and past five days of chatter, with CVEs displayed in descending order of activity. Tapping on a CVE provides details, and the ability to explore the CVE on Bluesky, Feedly, CIRCL’s Vuln Lookup, and — if present in our data — GreyNoise.

At the bottom of the page is a 30-day heatmap of CVE chatter. Tap on any populated square to see all the Bluesky chatter for that CVE.

This is similar to, but slightly different to the most excellent CVE Crowd, which monitors the Mastodonverse for CVE chatter.

The code behind the site also maintains a Bluesky list containing all the folks who chatter about CVEs on Bluesky.

Comments? Questions? Bugs? Feature requests? Hit up research@greynoise.io.

VulnCheck’s Free Community KEV & CVE APIs (Code & Golang CLI Utility)

VulnCheck has some new, free API endpoints for the cybersecurity community.

Two extremely useful ones are for their extended version of CISA’s KEV, and an in-situ replacement for NVD’s sad excuse for an API and soon-to-be-removed JSON feeds.

There are two ways to work with these APIs. One is retrieve a “backup” of the entire dataset as a ZIP file, and the other is to use the API to retrieve individual CVEs from each “index”.

You’ll need a free API key from VulnCheck to use these APIs.

All code shown makes the assumption that you’ve stored your API key in an environment variable named VULNCHECK_API_KEY.

After the curl examples, there’s a section on a small Golang CLI I made to make it easier to get combined extended KEV and NVDv2 CVE information in one CLI call for a given CVE.

Backups

Retrieving the complete dataset is a multi-step process. First you make a call to the specific API endpoint for each index to backup. That returns some JSON with a temporary, AWS pre-signed URL (a method to grant temporary access to files stored in AWS S3) to download the ZIP file. Then you download the ZIP file, and finally you extract the contents of the ZIP file into a directory. The output is different for the NVDv2 and extended KEV indexes, but the core process is the same.

NVDv2

Here’s a curl idiom for the NVDv2 index backup. The result is a directory of uncompressed JSON that’s in the same format as the NVDv2 JSON feeds.

# Grab the temporary AWS pre-signed URL for the NVDv2 index and then download the ZIP file.
curl \
  --silent \
  --output vcnvd2.zip --url "$(
    curl \
      --silent \
      --cookie "token=${VULNCHECK_API_KEY}" \
      --header 'Accept: application/json' \
      --url "https://api.vulncheck.com/v3/backup/nist-nvd2" | jq -r '.data[].url'
    )"

rm -rf ./nvd2

# unzip it
unzip -q -o -d ./nvd2 vcnvd2.zip

# uncompress the JSON files
ls ./nvd2/*gz | xargs gunzip

tree ./nvd2

./nvd2
├── nvdcve-2.0-000.json
├── nvdcve-2.0-001.json
├── nvdcve-2.0-002.json
├── nvdcve-2.0-003.json
├── nvdcve-2.0-004.json
├── nvdcve-2.0-005.json
├── nvdcve-2.0-006.json
├── nvdcve-2.0-007.json
├── nvdcve-2.0-008.json
├── nvdcve-2.0-009.json
├── nvdcve-2.0-010.json
├── nvdcve-2.0-011.json
├── nvdcve-2.0-012.json
├── nvdcve-2.0-013.json
├── nvdcve-2.0-014.json
├── nvdcve-2.0-015.json
├── nvdcve-2.0-016.json
├── nvdcve-2.0-017.json
├── nvdcve-2.0-018.json
├── nvdcve-2.0-019.json
├── nvdcve-2.0-020.json
├── nvdcve-2.0-021.json
├── nvdcve-2.0-022.json
├── nvdcve-2.0-023.json
├── nvdcve-2.0-024.json
├── nvdcve-2.0-025.json
├── nvdcve-2.0-026.json
├── nvdcve-2.0-027.json
├── nvdcve-2.0-028.json
├── nvdcve-2.0-029.json
├── nvdcve-2.0-030.json
├── nvdcve-2.0-031.json
├── nvdcve-2.0-032.json
├── nvdcve-2.0-033.json
├── nvdcve-2.0-034.json
├── nvdcve-2.0-035.json
├── nvdcve-2.0-036.json
├── nvdcve-2.0-037.json
├── nvdcve-2.0-038.json
├── nvdcve-2.0-039.json
├── nvdcve-2.0-040.json
├── nvdcve-2.0-041.json
├── nvdcve-2.0-042.json
├── nvdcve-2.0-043.json
├── nvdcve-2.0-044.json
├── nvdcve-2.0-045.json
├── nvdcve-2.0-046.json
├── nvdcve-2.0-047.json
├── nvdcve-2.0-048.json
├── nvdcve-2.0-049.json
├── nvdcve-2.0-050.json
├── nvdcve-2.0-051.json
├── nvdcve-2.0-052.json
├── nvdcve-2.0-053.json
├── nvdcve-2.0-054.json
├── nvdcve-2.0-055.json
├── nvdcve-2.0-056.json
├── nvdcve-2.0-057.json
├── nvdcve-2.0-058.json
├── nvdcve-2.0-059.json
├── nvdcve-2.0-060.json
├── nvdcve-2.0-061.json
├── nvdcve-2.0-062.json
├── nvdcve-2.0-063.json
├── nvdcve-2.0-064.json
├── nvdcve-2.0-065.json
├── nvdcve-2.0-066.json
├── nvdcve-2.0-067.json
├── nvdcve-2.0-068.json
├── nvdcve-2.0-069.json
├── nvdcve-2.0-070.json
├── nvdcve-2.0-071.json
├── nvdcve-2.0-072.json
├── nvdcve-2.0-073.json
├── nvdcve-2.0-074.json
├── nvdcve-2.0-075.json
├── nvdcve-2.0-076.json
├── nvdcve-2.0-077.json
├── nvdcve-2.0-078.json
├── nvdcve-2.0-079.json
├── nvdcve-2.0-080.json
├── nvdcve-2.0-081.json
├── nvdcve-2.0-082.json
├── nvdcve-2.0-083.json
├── nvdcve-2.0-084.json
├── nvdcve-2.0-085.json
├── nvdcve-2.0-086.json
├── nvdcve-2.0-087.json
├── nvdcve-2.0-088.json
├── nvdcve-2.0-089.json
├── nvdcve-2.0-090.json
├── nvdcve-2.0-091.json
├── nvdcve-2.0-092.json
├── nvdcve-2.0-093.json
├── nvdcve-2.0-094.json
├── nvdcve-2.0-095.json
├── nvdcve-2.0-096.json
├── nvdcve-2.0-097.json
├── nvdcve-2.0-098.json
├── nvdcve-2.0-099.json
├── nvdcve-2.0-100.json
├── nvdcve-2.0-101.json
├── nvdcve-2.0-102.json
├── nvdcve-2.0-103.json
├── nvdcve-2.0-104.json
├── nvdcve-2.0-105.json
├── nvdcve-2.0-106.json
├── nvdcve-2.0-107.json
├── nvdcve-2.0-108.json
├── nvdcve-2.0-109.json
├── nvdcve-2.0-110.json
├── nvdcve-2.0-111.json
├── nvdcve-2.0-112.json
├── nvdcve-2.0-113.json
├── nvdcve-2.0-114.json
├── nvdcve-2.0-115.json
├── nvdcve-2.0-116.json
├── nvdcve-2.0-117.json
├── nvdcve-2.0-118.json
├── nvdcve-2.0-119.json
├── nvdcve-2.0-120.json
└── nvdcve-2.0-121.json

1 directory, 122 files

VulnCheck’s Extended KEV

Here’s a curl idiom for the extended KEV index backup. The result is a directory with a single uncompressed JSON that’s in an extended format of what’s in the CISA KEV JSON.s

# Grab the temporary AWS pre-signed URL for the NVDv2 index and then download the ZIP file.
curl \
  --silent \
  --output vckev.zip --url "$(
    curl \
      --silent \
      --cookie "token=${VULNCHECK_API_KEY}" \
      --header 'Accept: application/json' \
      --url "https://api.vulncheck.com/v3/backup/vulncheck-kev" | jq -r '.data[].url'
    )"

rm -rf ./vckev

# unzip it
unzip -q -o -d ./vckev vckev.zip

tree ./vckev

./vckev
└── vulncheck_known_exploited_vulnerabilities.json

1 directory, 1 file

Retrieving Information On Individual CVEs

While there are other, searchable fields for each index, the primary use case for most of us is getting information on individual CVEs. The API calls are virtually identical, apart from the selected index.

NOTE: the examples pipe the output through jq to make the API results easier to read.

NVDv2

curl \
  --silent \
  --cookie "token=${VULNCHECK_API_KEY}" \
  --header 'Accept: application/json' \
  --url "https://api.vulncheck.com/v3/index/nist-nvd2?cve=CVE-2024-23334" | jq

{
  "_benchmark": 0.056277,
  "_meta": {
    "timestamp": "2024-03-23T08:47:17.940032202Z",
    "index": "nist-nvd2",
    "limit": 100,
    "total_documents": 1,
    "sort": "_id",
    "parameters": [
      {
        "name": "cve",
        "format": "CVE-YYYY-N{4-7}"
      },
      {
        "name": "alias"
      },
      {
        "name": "iava",
        "format": "[0-9]{4}[A-Z-0-9]+"
      },
      {
        "name": "threat_actor"
      },
      {
        "name": "mitre_id"
      },
      {
        "name": "misp_id"
      },
      {
        "name": "ransomware"
      },
      {
        "name": "botnet"
      },
      {
        "name": "published"
      },
      {
        "name": "lastModStartDate",
        "format": "YYYY-MM-DD"
      },
      {
        "name": "lastModEndDate",
        "format": "YYYY-MM-DD"
      }
    ],
    "order": "desc",
    "page": 1,
    "total_pages": 1,
    "max_pages": 6,
    "first_item": 1,
    "last_item": 1
  },
  "data": [
    {
      "id": "CVE-2024-23334",
      "sourceIdentifier": "security-advisories@github.com",
      "vulnStatus": "Modified",
      "published": "2024-01-29T23:15:08.563",
      "lastModified": "2024-02-09T03:15:09.603",
      "descriptions": [
        {
          "lang": "en",
          "value": "aiohttp is an asynchronous HTTP client/server framework for asyncio and Python. When using aiohttp as a web server and configuring static routes, it is necessary to specify the root path for static files. Additionally, the option 'follow_symlinks' can be used to determine whether to follow symbolic links outside the static root directory. When 'follow_symlinks' is set to True, there is no validation to check if reading a file is within the root directory. This can lead to directory traversal vulnerabilities, resulting in unauthorized access to arbitrary files on the system, even when symlinks are not present.  Disabling follow_symlinks and using a reverse proxy are encouraged mitigations.  Version 3.9.2 fixes this issue."
        },
        {
          "lang": "es",
          "value": "aiohttp es un framework cliente/servidor HTTP asíncrono para asyncio y Python. Cuando se utiliza aiohttp como servidor web y se configuran rutas estáticas, es necesario especificar la ruta raíz para los archivos estáticos. Además, la opción 'follow_symlinks' se puede utilizar para determinar si se deben seguir enlaces simbólicos fuera del directorio raíz estático. Cuando 'follow_symlinks' se establece en Verdadero, no hay validación para verificar si la lectura de un archivo está dentro del directorio raíz. Esto puede generar vulnerabilidades de directory traversal, lo que resulta en acceso no autorizado a archivos arbitrarios en el sistema, incluso cuando no hay enlaces simbólicos presentes. Se recomiendan como mitigaciones deshabilitar follow_symlinks y usar un proxy inverso. La versión 3.9.2 soluciona este problema."
        }
      ],
      "references": [
        {
          "url": "https://github.com/aio-libs/aiohttp/commit/1c335944d6a8b1298baf179b7c0b3069f10c514b",
          "source": "security-advisories@github.com",
          "tags": [
            "Patch"
          ]
        },
        {
          "url": "https://github.com/aio-libs/aiohttp/pull/8079",
          "source": "security-advisories@github.com",
          "tags": [
            "Patch"
          ]
        },
        {
          "url": "https://github.com/aio-libs/aiohttp/security/advisories/GHSA-5h86-8mv2-jq9f",
          "source": "security-advisories@github.com",
          "tags": [
            "Exploit",
            "Mitigation",
            "Vendor Advisory"
          ]
        },
        {
          "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/ICUOCFGTB25WUT336BZ4UNYLSZOUVKBD/",
          "source": "security-advisories@github.com"
        },
        {
          "url": "https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/XXWVZIVAYWEBHNRIILZVB3R3SDQNNAA7/",
          "source": "security-advisories@github.com",
          "tags": [
            "Mailing List"
          ]
        }
      ],
      "metrics": {
        "cvssMetricV31": [
          {
            "source": "nvd@nist.gov",
            "type": "Primary",
            "cvssData": {
              "version": "3.1",
              "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N",
              "attackVector": "NETWORK",
              "attackComplexity": "LOW",
              "privilegesRequired": "NONE",
              "userInteraction": "NONE",
              "scope": "UNCHANGED",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "NONE",
              "availabilityImpact": "NONE",
              "baseScore": 7.5,
              "baseSeverity": "HIGH"
            },
            "exploitabilityScore": 3.9,
            "impactScore": 3.6
          },
          {
            "source": "security-advisories@github.com",
            "type": "Secondary",
            "cvssData": {
              "version": "3.1",
              "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N",
              "attackVector": "NETWORK",
              "attackComplexity": "HIGH",
              "privilegesRequired": "NONE",
              "userInteraction": "NONE",
              "scope": "UNCHANGED",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "NONE",
              "availabilityImpact": "NONE",
              "baseScore": 5.9,
              "baseSeverity": "MEDIUM"
            },
            "exploitabilityScore": 2.2,
            "impactScore": 3.6
          }
        ]
      },
      "weaknesses": [
        {
          "source": "security-advisories@github.com",
          "type": "Primary",
          "description": [
            {
              "lang": "en",
              "value": "CWE-22"
            }
          ]
        }
      ],
      "configurations": [
        {
          "nodes": [
            {
              "operator": "OR",
              "cpeMatch": [
                {
                  "vulnerable": true,
                  "criteria": "cpe:2.3:a:aiohttp:aiohttp:*:*:*:*:*:*:*:*",
                  "versionStartIncluding": "1.0.5",
                  "versionEndExcluding": "3.9.2",
                  "matchCriteriaId": "CC18B2A9-9D80-4A6E-94E7-8FC010D8FC70"
                }
              ]
            }
          ]
        },
        {
          "nodes": [
            {
              "operator": "OR",
              "cpeMatch": [
                {
                  "vulnerable": true,
                  "criteria": "cpe:2.3:o:fedoraproject:fedora:39:*:*:*:*:*:*:*",
                  "matchCriteriaId": "B8EDB836-4E6A-4B71-B9B2-AA3E03E0F646"
                }
              ]
            }
          ]
        }
      ],
      "_timestamp": "2024-02-09T05:33:33.170054Z"
    }
  ]
}

VulnCheck’s Extended KEV

curl \
  --silent \
  --cookie "token=${VULNCHECK_API_KEY}" \
  --header 'Accept: application/json' \
  --url "https://api.vulncheck.com/v3/index/vulncheck-kev?cve=CVE-2024-23334" | jq

{
  "_benchmark": 0.328855,
  "_meta": {
    "timestamp": "2024-03-23T08:47:41.025967418Z",
    "index": "vulncheck-kev",
    "limit": 100,
    "total_documents": 1,
    "sort": "_id",
    "parameters": [
      {
        "name": "cve",
        "format": "CVE-YYYY-N{4-7}"
      },
      {
        "name": "alias"
      },
      {
        "name": "iava",
        "format": "[0-9]{4}[A-Z-0-9]+"
      },
      {
        "name": "threat_actor"
      },
      {
        "name": "mitre_id"
      },
      {
        "name": "misp_id"
      },
      {
        "name": "ransomware"
      },
      {
        "name": "botnet"
      },
      {
        "name": "published"
      },
      {
        "name": "lastModStartDate",
        "format": "YYYY-MM-DD"
      },
      {
        "name": "lastModEndDate",
        "format": "YYYY-MM-DD"
      },
      {
        "name": "pubStartDate",
        "format": "YYYY-MM-DD"
      },
      {
        "name": "pubEndDate",
        "format": "YYYY-MM-DD"
      }
    ],
    "order": "desc",
    "page": 1,
    "total_pages": 1,
    "max_pages": 6,
    "first_item": 1,
    "last_item": 1
  },
  "data": [
    {
      "vendorProject": "aiohttp",
      "product": "aiohttp",
      "shortDescription": "aiohttp is an asynchronous HTTP client/server framework for asyncio and Python. When using aiohttp as a web server and configuring static routes, it is necessary to specify the root path for static files. Additionally, the option 'follow_symlinks' can be used to determine whether to follow symbolic links outside the static root directory. When 'follow_symlinks' is set to True, there is no validation to check if reading a file is within the root directory. This can lead to directory traversal vulnerabilities, resulting in unauthorized access to arbitrary files on the system, even when symlinks are not present.  Disabling follow_symlinks and using a reverse proxy are encouraged mitigations.  Version 3.9.2 fixes this issue.",
      "vulnerabilityName": "aiohttp aiohttp Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')",
      "required_action": "Apply remediations or mitigations per vendor instructions or discontinue use of the product if remediation or mitigations are unavailable.",
      "knownRansomwareCampaignUse": "Known",
      "cve": [
        "CVE-2024-23334"
      ],
      "vulncheck_xdb": [
        {
          "xdb_id": "231b48941355",
          "xdb_url": "https://vulncheck.com/xdb/231b48941355",
          "date_added": "2024-02-28T22:30:21Z",
          "exploit_type": "infoleak",
          "clone_ssh_url": "git@github.com:ox1111/CVE-2024-23334.git"
        },
        {
          "xdb_id": "f1d001911304",
          "xdb_url": "https://vulncheck.com/xdb/f1d001911304",
          "date_added": "2024-03-19T16:28:56Z",
          "exploit_type": "infoleak",
          "clone_ssh_url": "git@github.com:jhonnybonny/CVE-2024-23334.git"
        }
      ],
      "vulncheck_reported_exploitation": [
        {
          "url": "https://cyble.com/blog/cgsi-probes-shadowsyndicate-groups-possible-exploitation-of-aiohttp-vulnerability-cve-2024-23334/",
          "date_added": "2024-03-15T00:00:00Z"
        }
      ],
      "date_added": "2024-03-15T00:00:00Z",
      "_timestamp": "2024-03-23T08:27:47.861266Z"
    }
  ]
}

vccve

There’s a project on Codeberg that has code and binaries for macOS, Linux, and Windows for a small CLI that gets you combined extended KEV and NVDv2 information all in one call.

The project README has examples and installation instructions.

Avoid libwebp Electron Woes On macOS With positron

If you’ve got 👀 on this blog (directly, or via syndication) you’d have to have been living under a rock to not know about the libwebp supply chain disaster. An unfortunate casualty of inept programming just happened to be any app in the Electron ecosystem that doesn’t undergo bleeding-edge updates.

Former cow-orker Tom Sellers (one of the best humans in cyber) did a great service to the macOS user community with tips on how to stay safe on macOS. His find + strings + grep combo was superbly helpful and I hope many macOS users did the command line dance to see how negligent their app providers were/are.

But, you still have to know what versions are OK and which ones are not to do that dance. And, having had yet-another immune system invasion (thankfully, not COVID, again) on top of still working through long COVID (#protip: you may be over the pandemic, but I guarantee it’s not done with you/us for a while) which re-sapped mobility energy, I put my sedentary time to less woesome use by hacking together a small, Golang macOS CLI to help ferret out bad Electron-based apps you may have installed.

I named it positron, since that’s kind of the opposite of Electron, and I was pretty creativity-challenged today.

It does virtually the same thing as Tom’s strings and grep does, just in a single, lightweight, universal, signed macOS binary.

When I ran it after the final build, all my Electron-based apps were 🔴. After deleting some, and updating others, this is my current status:

$ find /Applications -type f -name "*Electron Framework*" -exec ./positron "{}" \;
/Applications/Signal.app: Chrome/114.0.5735.289 Electron/25.8.4 🟢
/Applications/Keybase.app: Chrome/87.0.4280.141 Electron/11.5.0 🔴
/Applications/Raindrop.io.app: Chrome/102.0.5005.167 Electron/19.0.17 🔴
/Applications/1Password.app: Chrome/114.0.5735.289 Electron/25.8.1 🟢
/Applications/Replit.app: Chrome/116.0.5845.188 Electron/26.2.1 🟢
/Applications/lghub.app: Chrome/104.0.5112.65 Electron/20.0.0 🔴

It’s still on you to do the find (cooler folks run fd) since I’m not about to write a program that’ll rummage across your SSDs or disc drives, but it does all the MachO inspection internally, and then also does the SemVer comparison to let you know which apps still suck at keeping you safe.

FWIW, the Keybase folks did accept a PR for the libwebp thing, but darned if I will spend any time building it (I don’t run it anymore, anyway, so I should just delete it).

The aforementioned signed, universal, macOS binary is in the GitLab releases.

Stay safe out there!

Acoustic: Solving a CyberDefenders PCAP SIP/RTP Challenge with R, Zeek, tshark (& friends)

Hot on the heels of the previous CyberDefenders Challenge Solution comes this noisy installment which solves their Acoustic challenge.

You can find the source Rmd on GitHub, but I’m also testing the limits of WP’s markdown rendering and putting it in-stream as well.

No longer book expository this time since much of the setup/explanatory bits from it apply here as well).

Acoustic

This challenge takes us “into the world of voice communications on the internet. VoIP is becoming the de-facto standard for voice communication. As this technology becomes more common, malicious parties have more opportunities and stronger motives to control these systems to conduct nefarious activities. This challenge was designed to examine and explore some of the attributes of the SIP and RTP protocols.”

We have two files to work with:

  • log.txt which was generated from an unadvertised, passive honeypot located on the internet such that any traffic destined to it must be nefarious. Unknown parties scanned the honeypot with a range of tools, and this activity is represented in the log file.
    • The IP address of the honeypot has been changed to “honey.pot.IP.removed”. In terms of geolocation, pick your favorite city.
    • The MD5 hash in the authorization digest is replaced with “MD5_hash_removedXXXXXXXXXXXXXXXX”
    • Some octets of external IP addresses have been replaced with an “X”
    • Several trailing digits of phone numbers have been replaced with an “X”
    • Assume the timestamps in the log files are UTC.
  • Voip-trace.pcap was created by honeynet members for this forensic challenge to allow participants to employ network analysis skills in the VOIP context.

There are 14 questions to answer.

If you are not familiar with SIP and/or RTP you should do a bit of research first. A good place to start is RTC 3261 (for SIP) and RFC 3550 (for RTC). Some questions may be able to be answered just by knowing the details of these protocols.

Convert the PCAP

library(stringi)
library(tidyverse)

We’ll pre-generate Zeek logs. The -C tells Zeek to not bother with checksums, -r tells it to read from a file and the LogAscii::use_json=T means we want JSON output vs the default delimited files. JSON gives us data types (the headers in the delimited files do as well, but we’d have to write something to read those types then deal with it vs get this for free out of the box with JSON).

system("ZEEK_LOG_SUFFIX=json /opt/zeek/bin/zeek -C -r src/Voip-trace.pcap LogAscii::use_json=T HTTP::default_capture_password=T")

We process the PCAP twice with tshark. Once to get the handy (and small) packet summary table, then dump the whole thing to JSON. We may need to run tshark again down the road a bit.

system("tshark -T tabs -r src/Voip-trace.pcap > voip-packets.tsv")
system("tshark -T json -r src/Voip-trace.pcap > voip-trace")

Examine and Process log.txt

We aren’t told what format log.txt is in, so let’s take a look:

cd_sip_log <- stri_read_lines("src/log.txt")

cat(head(cd_sip_log, 25), sep="\n")
## Source: 210.184.X.Y:1083
## Datetime: 2010-05-02 01:43:05.606584
## 
## Message:
## 
## OPTIONS sip:100@honey.pot.IP.removed SIP/2.0
## Via: SIP/2.0/UDP 127.0.0.1:5061;branch=z9hG4bK-2159139916;rport
## Content-Length: 0
## From: "sipvicious"<sip:100@1.1.1.1>; tag=X_removed
## Accept: application/sdp
## User-Agent: friendly-scanner
## To: "sipvicious"<sip:100@1.1.1.1>
## Contact: sip:100@127.0.0.1:5061
## CSeq: 1 OPTIONS
## Call-ID: 845752980453913316694142
## Max-Forwards: 70
## 
## 
## 
## 
## -------------------------
## Source: 210.184.X.Y:4956
## Datetime: 2010-05-02 01:43:12.488811
## 
## Message:

These look a bit like HTTP server responses, but we know we’re working in SIP land and if you perused the RFC you’d have noticed that SIP is an HTTP-like ASCII protocol. While some HTTP response parsers might work on these records, it’s pretty straightforward to whip up a bespoke pseudo-parser.

Let’s see how many records there are by counting the number of “Message:” lines (we’re doing this, primarily, to see if we should use the {furrr} package to speed up processing):

cd_sip_log[stri_detect_fixed(cd_sip_log, "Message:")] %>%
  table()
## .
## Message: 
##     4266

There are many, so we’ll avoid parallel processing the data and just use a single thread.

One way to tackle the parsing is to look for the stop and start of each record, extract fields (these have similar formats to HTTP headers), and perhaps have to extract content as well. We know this because there are “Content-Length:” fields. According to the RFC they are supposed to exist for every message. Let’s first see if any “Content-Length:” header records are greater than 0. We’ll do this with a little help from the ripgrep utility as it provides a way to see context before and/or after matched patterns:

cat(system('rg --after-context=10 "^Content-Length: [^0]" src/log.txt', intern=TRUE), sep="\n")
## Content-Length: 330
## 
## v=0
## o=Zoiper_user 0 0 IN IP4 89.42.194.X
## s=Zoiper_session
## c=IN IP4 89.42.194.X
## t=0 0
## m=audio 52999 RTP/AVP 3 0 8 110 98 101
## a=rtpmap:3 GSM/8000
## a=rtpmap:0 PCMU/8000
## a=rtpmap:8 PCMA/8000
## --
## Content-Length: 330
## 
## v=0
## o=Zoiper_user 0 0 IN IP4 89.42.194.X
## s=Zoiper_session
## c=IN IP4 89.42.194.X
## t=0 0
## m=audio 52999 RTP/AVP 3 0 8 110 98 101
## a=rtpmap:3 GSM/8000
## a=rtpmap:0 PCMU/8000
## a=rtpmap:8 PCMA/8000
## --
## Content-Length: 330
## 
## v=0
## o=Zoiper_user 0 0 IN IP4 89.42.194.X
## s=Zoiper_session
## c=IN IP4 89.42.194.X
## t=0 0
## m=audio 52999 RTP/AVP 3 0 8 110 98 101
## a=rtpmap:3 GSM/8000
## a=rtpmap:0 PCMU/8000
## a=rtpmap:8 PCMA/8000
## --
## Content-Length: 330
## 
## v=0
## o=Zoiper_user 0 0 IN IP4 89.42.194.X
## s=Zoiper_session
## c=IN IP4 89.42.194.X
## t=0 0
## m=audio 52999 RTP/AVP 3 0 8 110 98 101
## a=rtpmap:3 GSM/8000
## a=rtpmap:0 PCMU/8000
## a=rtpmap:8 PCMA/8000

So,we do need to account for content. It’s still pretty straightforward (explanatory comments inline):

starts <- which(stri_detect_regex(cd_sip_log, "^Source:"))
stops <- which(stri_detect_regex(cd_sip_log, "^----------"))

map2_dfr(starts, stops, ~{

  raw_rec <- stri_trim_both(cd_sip_log[.x:.y]) # target the record from the log
  raw_rec <- raw_rec[raw_rec != "-------------------------"] # remove separator

  msg_idx <- which(stri_detect_regex(raw_rec, "^Message:")) # find where "Message:" line is
  source_idx <- which(stri_detect_regex(raw_rec, "^Source: ")) # find where "Source:" line is
  datetime_idx <- which(stri_detect_regex(raw_rec, "^Datetime: ")) # find where "Datetime:" line is
  contents_idx <- which(stri_detect_regex(raw_rec[(msg_idx+2):length(raw_rec)], "^$"))[1] + 2 # get position of the "data"

  source <- stri_match_first_regex(raw_rec[source_idx], "^Source: (.*)$")[,2] # extract source
  datetime <- stri_match_first_regex(raw_rec[datetime_idx], "^Datetime: (.*)$")[,2] # extract datetime
  request <- raw_rec[msg_idx+2] # extract request line

  # build a matrix out of the remaining headers. header key will be in column 2, value will be in column 3
  tmp <- stri_match_first_regex(raw_rec[(msg_idx+3):contents_idx], "^([^:]+):[[:space:]]+(.*)$")
  tmp[,2] <- stri_trans_tolower(tmp[,2]) # lowercase the header key
  tmp[,2] <- stri_replace_all_fixed(tmp[,2], "-", "_") # turn dashes to underscores so we can more easily use the keys as column names

  contents <- raw_rec[(contents_idx+1):length(raw_rec)]
  contents <- paste0(contents[contents != ""], collapse = "\n")

  as.list(tmp[,3]) %>% # turn the header values into a list
    set_names(tmp[,2]) %>% # make their names the tranformed keys
    append(c(
      source = source, # add source to the list (etc)
      datetime = datetime,
      request = request,
      contents = contents
    ))

}) -> sip_log_parsed

Let’s see what we have:

sip_log_parsed
## # A tibble: 4,266 x 18
##    via     content_length from    accept  user_agent to     contact cseq  source
##    <chr>   <chr>          <chr>   <chr>   <chr>      <chr>  <chr>   <chr> <chr> 
##  1 SIP/2.… 0              "\"sip… applic… friendly-… "\"si… sip:10… 1 OP… 210.1…
##  2 SIP/2.… 0              "\"342… applic… friendly-… "\"34… sip:34… 1 RE… 210.1…
##  3 SIP/2.… 0              "\"172… applic… friendly-… "\"17… sip:17… 1 RE… 210.1…
##  4 SIP/2.… 0              "\"adm… applic… friendly-… "\"ad… sip:ad… 1 RE… 210.1…
##  5 SIP/2.… 0              "\"inf… applic… friendly-… "\"in… sip:in… 1 RE… 210.1…
##  6 SIP/2.… 0              "\"tes… applic… friendly-… "\"te… sip:te… 1 RE… 210.1…
##  7 SIP/2.… 0              "\"pos… applic… friendly-… "\"po… sip:po… 1 RE… 210.1…
##  8 SIP/2.… 0              "\"sal… applic… friendly-… "\"sa… sip:sa… 1 RE… 210.1…
##  9 SIP/2.… 0              "\"ser… applic… friendly-… "\"se… sip:se… 1 RE… 210.1…
## 10 SIP/2.… 0              "\"sup… applic… friendly-… "\"su… sip:su… 1 RE… 210.1…
## # … with 4,256 more rows, and 9 more variables: datetime <chr>, request <chr>,
## #   contents <chr>, call_id <chr>, max_forwards <chr>, expires <chr>,
## #   allow <chr>, authorization <chr>, content_type <chr>

glimpse(sip_log_parsed)
## Rows: 4,266
## Columns: 18
## $ via            <chr> "SIP/2.0/UDP 127.0.0.1:5061;branch=z9hG4bK-2159139916;r…
## $ content_length <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", …
## $ from           <chr> "\"sipvicious\"<sip:100@1.1.1.1>; tag=X_removed", "\"34…
## $ accept         <chr> "application/sdp", "application/sdp", "application/sdp"…
## $ user_agent     <chr> "friendly-scanner", "friendly-scanner", "friendly-scann…
## $ to             <chr> "\"sipvicious\"<sip:100@1.1.1.1>", "\"3428948518\"<sip:…
## $ contact        <chr> "sip:100@127.0.0.1:5061", "sip:3428948518@honey.pot.IP.…
## $ cseq           <chr> "1 OPTIONS", "1 REGISTER", "1 REGISTER", "1 REGISTER", …
## $ source         <chr> "210.184.X.Y:1083", "210.184.X.Y:4956", "210.184.X.Y:51…
## $ datetime       <chr> "2010-05-02 01:43:05.606584", "2010-05-02 01:43:12.4888…
## $ request        <chr> "OPTIONS sip:100@honey.pot.IP.removed SIP/2.0", "REGIST…
## $ contents       <chr> "Call-ID: 845752980453913316694142\nMax-Forwards: 70", …
## $ call_id        <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ max_forwards   <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ expires        <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ allow          <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ authorization  <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ content_type   <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…

Looks 👍, but IRL there are edge-cases we’d have to deal with.

Process Zeek Logs

Because they’re JSON files, and the names are reasonable, we can do some magic incantations to read them all in and shove them into a list we’ll call zeek:

zeek <- list()

list.files(
  pattern = "json$",
  full.names = TRUE
) %>%
  walk(~{
    append(zeek, list(file(.x) %>% 
      jsonlite::stream_in(verbose = FALSE) %>%
      as_tibble()) %>% 
        set_names(tools::file_path_sans_ext(basename(.x)))
    ) ->> zeek
  })

str(zeek, 1)
## List of 7
##  $ conn         : tibble [97 × 18] (S3: tbl_df/tbl/data.frame)
##  $ dpd          : tibble [1 × 9] (S3: tbl_df/tbl/data.frame)
##  $ files        : tibble [38 × 16] (S3: tbl_df/tbl/data.frame)
##  $ http         : tibble [92 × 24] (S3: tbl_df/tbl/data.frame)
##  $ packet_filter: tibble [1 × 5] (S3: tbl_df/tbl/data.frame)
##  $ sip          : tibble [9 × 23] (S3: tbl_df/tbl/data.frame)
##  $ weird        : tibble [1 × 9] (S3: tbl_df/tbl/data.frame)

walk2(names(zeek), zeek, ~{
  cat("File:", .x, "\n")
  glimpse(.y)
  cat("\n\n")
})
## File: conn 
## Rows: 97
## Columns: 18
## $ ts            <dbl> 1272737631, 1272737581, 1272737669, 1272737669, 12727376…
## $ uid           <chr> "Cb0OAQ1eC0ZhQTEKNl", "C2s0IU2SZFGVlZyH43", "CcEeLRD3cca…
## $ id.orig_h     <chr> "172.25.105.43", "172.25.105.43", "172.25.105.43", "172.…
## $ id.orig_p     <int> 57086, 5060, 57087, 57088, 57089, 57090, 57091, 57093, 5…
## $ id.resp_h     <chr> "172.25.105.40", "172.25.105.40", "172.25.105.40", "172.…
## $ id.resp_p     <int> 80, 5060, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80…
## $ proto         <chr> "tcp", "udp", "tcp", "tcp", "tcp", "tcp", "tcp", "tcp", …
## $ service       <chr> "http", "sip", "http", "http", "http", "http", "http", "…
## $ duration      <dbl> 0.0180180073, 0.0003528595, 0.0245900154, 0.0740420818, …
## $ orig_bytes    <int> 502, 428, 380, 385, 476, 519, 520, 553, 558, 566, 566, 5…
## $ resp_bytes    <int> 720, 518, 231, 12233, 720, 539, 17499, 144, 144, 144, 14…
## $ conn_state    <chr> "SF", "SF", "SF", "SF", "SF", "SF", "SF", "SF", "SF", "S…
## $ missed_bytes  <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ history       <chr> "ShADadfF", "Dd", "ShADadfF", "ShADadfF", "ShADadfF", "S…
## $ orig_pkts     <int> 5, 1, 5, 12, 5, 6, 16, 6, 6, 5, 5, 5, 5, 5, 5, 5, 6, 5, …
## $ orig_ip_bytes <int> 770, 456, 648, 1017, 744, 839, 1360, 873, 878, 834, 834,…
## $ resp_pkts     <int> 5, 1, 5, 12, 5, 5, 16, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, …
## $ resp_ip_bytes <int> 988, 546, 499, 12865, 988, 807, 18339, 412, 412, 412, 41…
## 
## 
## File: dpd 
## Rows: 1
## Columns: 9
## $ ts             <dbl> 1272737798
## $ uid            <chr> "CADvMziC96POynR2e"
## $ id.orig_h      <chr> "172.25.105.3"
## $ id.orig_p      <int> 43204
## $ id.resp_h      <chr> "172.25.105.40"
## $ id.resp_p      <int> 5060
## $ proto          <chr> "udp"
## $ analyzer       <chr> "SIP"
## $ failure_reason <chr> "Binpac exception: binpac exception: string mismatch at…
## 
## 
## File: files 
## Rows: 38
## Columns: 16
## $ ts             <dbl> 1272737631, 1272737669, 1272737676, 1272737688, 1272737…
## $ fuid           <chr> "FRnb7P5EDeZE4Y3z4", "FOT2gC2yLxjfMCuE5f", "FmUCuA3dzcS…
## $ tx_hosts       <list> "172.25.105.40", "172.25.105.40", "172.25.105.40", "17…
## $ rx_hosts       <list> "172.25.105.43", "172.25.105.43", "172.25.105.43", "17…
## $ conn_uids      <list> "Cb0OAQ1eC0ZhQTEKNl", "CFfYtA0DqqrJk4gI5", "CHN4qA4UUH…
## $ source         <chr> "HTTP", "HTTP", "HTTP", "HTTP", "HTTP", "HTTP", "HTTP",…
## $ depth          <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ analyzers      <list> [], [], [], [], [], [], [], [], [], [], [], [], [], []…
## $ mime_type      <chr> "text/html", "text/html", "text/html", "text/html", "te…
## $ duration       <dbl> 0.000000e+00, 8.920908e-03, 0.000000e+00, 0.000000e+00,…
## $ is_orig        <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, …
## $ seen_bytes     <int> 479, 11819, 479, 313, 17076, 55, 50, 30037, 31608, 1803…
## $ total_bytes    <int> 479, NA, 479, 313, NA, 55, 50, NA, NA, NA, 58, 313, 50,…
## $ missing_bytes  <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ overflow_bytes <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ timedout       <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,…
## 
## 
## File: http 
## Rows: 92
## Columns: 24
## $ ts                <dbl> 1272737631, 1272737669, 1272737669, 1272737676, 1272…
## $ uid               <chr> "Cb0OAQ1eC0ZhQTEKNl", "CcEeLRD3cca3j4QGh", "CFfYtA0D…
## $ id.orig_h         <chr> "172.25.105.43", "172.25.105.43", "172.25.105.43", "…
## $ id.orig_p         <int> 57086, 57087, 57088, 57089, 57090, 57091, 57093, 570…
## $ id.resp_h         <chr> "172.25.105.40", "172.25.105.40", "172.25.105.40", "…
## $ id.resp_p         <int> 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, …
## $ trans_depth       <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1…
## $ method            <chr> "GET", "GET", "GET", "GET", "GET", "GET", "GET", "GE…
## $ host              <chr> "172.25.105.40", "172.25.105.40", "172.25.105.40", "…
## $ uri               <chr> "/maint", "/", "/user/", "/maint", "/maint", "/maint…
## $ referrer          <chr> "http://172.25.105.40/user/", NA, NA, "http://172.25…
## $ version           <chr> "1.1", "1.1", "1.1", "1.1", "1.1", "1.1", "1.1", "1.…
## $ user_agent        <chr> "Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.9.1.9)…
## $ request_body_len  <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ response_body_len <int> 479, 0, 11819, 479, 313, 17076, 0, 0, 0, 0, 0, 0, 0,…
## $ status_code       <int> 401, 302, 200, 401, 301, 200, 304, 304, 304, 304, 30…
## $ status_msg        <chr> "Authorization Required", "Found", "OK", "Authorizat…
## $ tags              <list> [], [], [], [], [], [], [], [], [], [], [], [], [],…
## $ resp_fuids        <list> "FRnb7P5EDeZE4Y3z4", <NULL>, "FOT2gC2yLxjfMCuE5f", …
## $ resp_mime_types   <list> "text/html", <NULL>, "text/html", "text/html", "tex…
## $ username          <chr> NA, NA, NA, NA, "maint", "maint", "maint", "maint", …
## $ password          <chr> NA, NA, NA, NA, "password", "password", "password", …
## $ orig_fuids        <list> <NULL>, <NULL>, <NULL>, <NULL>, <NULL>, <NULL>, <NU…
## $ orig_mime_types   <list> <NULL>, <NULL>, <NULL>, <NULL>, <NULL>, <NULL>, <NU…
## 
## 
## File: packet_filter 
## Rows: 1
## Columns: 5
## $ ts      <dbl> 1627151196
## $ node    <chr> "zeek"
## $ filter  <chr> "ip or not ip"
## $ init    <lgl> TRUE
## $ success <lgl> TRUE
## 
## 
## File: sip 
## Rows: 9
## Columns: 23
## $ ts                <dbl> 1272737581, 1272737768, 1272737768, 1272737768, 1272…
## $ uid               <chr> "C2s0IU2SZFGVlZyH43", "CADvMziC96POynR2e", "CADvMziC…
## $ id.orig_h         <chr> "172.25.105.43", "172.25.105.3", "172.25.105.3", "17…
## $ id.orig_p         <int> 5060, 43204, 43204, 43204, 43204, 43204, 43204, 4320…
## $ id.resp_h         <chr> "172.25.105.40", "172.25.105.40", "172.25.105.40", "…
## $ id.resp_p         <int> 5060, 5060, 5060, 5060, 5060, 5060, 5060, 5060, 5060
## $ trans_depth       <int> 0, 0, 0, 0, 0, 0, 0, 0, 0
## $ method            <chr> "OPTIONS", "REGISTER", "REGISTER", "SUBSCRIBE", "SUB…
## $ uri               <chr> "sip:100@172.25.105.40", "sip:172.25.105.40", "sip:1…
## $ request_from      <chr> "\"sipvicious\"<sip:100@1.1.1.1>", "<sip:555@172.25.…
## $ request_to        <chr> "\"sipvicious\"<sip:100@1.1.1.1>", "<sip:555@172.25.…
## $ response_from     <chr> "\"sipvicious\"<sip:100@1.1.1.1>", "<sip:555@172.25.…
## $ response_to       <chr> "\"sipvicious\"<sip:100@1.1.1.1>;tag=as18cdb0c9", "<…
## $ call_id           <chr> "61127078793469957194131", "MzEwMmYyYWRiYTUxYTBhODY3…
## $ seq               <chr> "1 OPTIONS", "1 REGISTER", "2 REGISTER", "1 SUBSCRIB…
## $ request_path      <list> "SIP/2.0/UDP 127.0.1.1:5060", "SIP/2.0/UDP 172.25.10…
## $ response_path     <list> "SIP/2.0/UDP 127.0.1.1:5060", "SIP/2.0/UDP 172.25.10…
## $ user_agent        <chr> "UNfriendly-scanner - for demo purposes", "X-Lite B…
## $ status_code       <int> 200, 401, 200, 401, 404, 401, 100, 200, NA
## $ status_msg        <chr> "OK", "Unauthorized", "OK", "Unauthorized", "Not fo…
## $ request_body_len  <int> 0, 0, 0, 0, 0, 264, 264, 264, 0
## $ response_body_len <int> 0, 0, 0, 0, 0, 0, 0, 302, NA
## $ content_type      <chr> NA, NA, NA, NA, NA, NA, NA, "application/sdp", NA
## 
## 
## File: weird 
## Rows: 1
## Columns: 9
## $ ts        <dbl> 1272737805
## $ id.orig_h <chr> "172.25.105.3"
## $ id.orig_p <int> 0
## $ id.resp_h <chr> "172.25.105.40"
## $ id.resp_p <int> 0
## $ name      <chr> "truncated_IPv6"
## $ notice    <lgl> FALSE
## $ peer      <chr> "zeek"
## $ source    <chr> "IP"

Process Packet Summary

We won’t process the big JSON file tshark generated for us util we really have to, but we can read in the packet summary table now:

packet_cols <- c("packet_num", "ts", "src", "discard", "dst", "proto", "length", "info")

read_tsv(
  file = "voip-packets.tsv",
  col_names = packet_cols,
  col_types = "ddccccdc"
) %>%
  select(-discard) -> packets

packets
## # A tibble: 4,447 x 7
##    packet_num       ts src      dst     proto length info                       
##         <dbl>    <dbl> <chr>    <chr>   <chr>  <dbl> <chr>                      
##  1          1  0       172.25.… 172.25… SIP      470 Request: OPTIONS sip:100@1…
##  2          2  3.53e-4 172.25.… 172.25… SIP      560 Status: 200 OK |           
##  3          3  5.03e+1 172.25.… 172.25… TCP       74 57086 → 80 [SYN] Seq=0 Win…
##  4          4  5.03e+1 172.25.… 172.25… TCP       74 80 → 57086 [SYN, ACK] Seq=…
##  5          5  5.03e+1 172.25.… 172.25… TCP       66 57086 → 80 [ACK] Seq=1 Ack…
##  6          6  5.03e+1 172.25.… 172.25… HTTP     568 GET /maint HTTP/1.1        
##  7          7  5.03e+1 172.25.… 172.25… TCP       66 80 → 57086 [ACK] Seq=1 Ack…
##  8          8  5.03e+1 172.25.… 172.25… HTTP     786 HTTP/1.1 401 Authorization…
##  9          9  5.03e+1 172.25.… 172.25… TCP       66 80 → 57086 [FIN, ACK] Seq=…
## 10         10  5.03e+1 172.25.… 172.25… TCP       66 57086 → 80 [ACK] Seq=503 A…
## # … with 4,437 more rows

glimpse(packets)
## Rows: 4,447
## Columns: 7
## $ packet_num <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, …
## $ ts         <dbl> 0.000000, 0.000353, 50.317176, 50.317365, 50.320071, 50.329…
## $ src        <chr> "172.25.105.43", "172.25.105.40", "172.25.105.43", "172.25.…
## $ dst        <chr> "172.25.105.40", "172.25.105.43", "172.25.105.40", "172.25.…
## $ proto      <chr> "SIP", "SIP", "TCP", "TCP", "TCP", "HTTP", "TCP", "HTTP", "…
## $ length     <dbl> 470, 560, 74, 74, 66, 568, 66, 786, 66, 66, 66, 66, 74, 74,…
## $ info       <chr> "Request: OPTIONS sip:100@172.25.105.40 |", "Status: 200 OK…

What is the transport protocol being used?

SIP can use TCP or UDP and which transport it uses will be specified in the Via: header. Let’s take a look:

head(sip_log_parsed$via)
## [1] "SIP/2.0/UDP 127.0.0.1:5061;branch=z9hG4bK-2159139916;rport"
## [2] "SIP/2.0/UDP 127.0.0.1:5087;branch=z9hG4bK-1189344537;rport"
## [3] "SIP/2.0/UDP 127.0.0.1:5066;branch=z9hG4bK-2119091576;rport"
## [4] "SIP/2.0/UDP 127.0.0.1:5087;branch=z9hG4bK-3226446220;rport"
## [5] "SIP/2.0/UDP 127.0.0.1:5087;branch=z9hG4bK-1330901245;rport"
## [6] "SIP/2.0/UDP 127.0.0.1:5087;branch=z9hG4bK-945386205;rport"

Are they all UDP? We can find out by performing some light processing
on the via column:

sip_log_parsed %>% 
  select(via) %>% 
  mutate(
    transport = stri_match_first_regex(via, "^([^[:space:]]+)")[,2]
  ) %>% 
  count(transport, sort=TRUE)
## # A tibble: 1 x 2
##   transport       n
##   <chr>       <int>
## 1 SIP/2.0/UDP  4266

Looks like they’re all UDP. Question 1: ✅

The attacker used a bunch of scanning tools that belong to the same suite. Provide the name of the suite.

Don’t you, now, wish you had listen to your parents when they were telling you about the facts of SIP life when you were a wee pup?

We’ll stick with the SIP log to answer this one and peek back at the RFC to see that there’s a “User-Agent:” field which contains information about the client originating the request. Most scanners written by defenders identify themselves in User-Agent fields when those fields are available in a protocol exchange, and a large percentage of naive malicious folks are too daft to change this value (or leave it default to make you think they’re not behaving badly).

If you are a regular visitor to SIP land, you likely know the common SIP scanning tools. These are a few:

  • Nmap’s SIP library
  • Mr.SIP, a “SIP-Based Audit and Attack Tool”
  • SIPVicious, a “set of security tools that can be used to audit SIP based VoIP systems”
  • Sippts, a “set of tools to audit SIP based VoIP Systems”

(There are many more.)

Let’s see what user-agent was used in this log extract:

count(sip_log_parsed, user_agent, sort=TRUE)
## # A tibble: 3 x 2
##   user_agent           n
##   <chr>            <int>
## 1 friendly-scanner  4248
## 2 Zoiper rev.6751     14
## 3 <NA>                 4

The overwhelming majority are friendly-scanner. Let’s look at a few of those log entries:

sip_log_parsed %>% 
  filter(
    user_agent == "friendly-scanner"
  ) %>% 
  glimpse()
## Rows: 4,248
## Columns: 18
## $ via            <chr> "SIP/2.0/UDP 127.0.0.1:5061;branch=z9hG4bK-2159139916;r…
## $ content_length <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", …
## $ from           <chr> "\"sipvicious\"<sip:100@1.1.1.1>; tag=X_removed", "\"34…
## $ accept         <chr> "application/sdp", "application/sdp", "application/sdp"…
## $ user_agent     <chr> "friendly-scanner", "friendly-scanner", "friendly-scann…
## $ to             <chr> "\"sipvicious\"<sip:100@1.1.1.1>", "\"3428948518\"<sip:…
## $ contact        <chr> "sip:100@127.0.0.1:5061", "sip:3428948518@honey.pot.IP.…
## $ cseq           <chr> "1 OPTIONS", "1 REGISTER", "1 REGISTER", "1 REGISTER", …
## $ source         <chr> "210.184.X.Y:1083", "210.184.X.Y:4956", "210.184.X.Y:51…
## $ datetime       <chr> "2010-05-02 01:43:05.606584", "2010-05-02 01:43:12.4888…
## $ request        <chr> "OPTIONS sip:100@honey.pot.IP.removed SIP/2.0", "REGIST…
## $ contents       <chr> "Call-ID: 845752980453913316694142\nMax-Forwards: 70", …
## $ call_id        <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ max_forwards   <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ expires        <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ allow          <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ authorization  <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ content_type   <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…

Those from and to fields have an interesting name in them: “sipviscious”. You’ve seen that before, right at the beginning of this section.

Let’s do a quick check over at the SIPvicious repo just to make sure.

count(sip_log_parsed, user_agent)
## # A tibble: 3 x 2
##   user_agent           n
##   <chr>            <int>
## 1 friendly-scanner  4248
## 2 Zoiper rev.6751     14
## 3 <NA>                 4

“What is the User-Agent of the victim system?”

We only have partial data in the text log so we’ll have to look elsewhere (the PCAP) for this information. The “victim” is whatever was the target of a this SIP-based attack and we can look for SIP messages, user agents, and associated IPs in the PCAP thanks to tshark’s rich SIP filter library:

system("tshark -Q -T fields -e ip.src -e ip.dst -e sip.User-Agent -r src/Voip-trace.pcap 'sip.User-Agent'")

That first exchange is all we really need. We see our rude poker talking to 172.25.105.40 and it responding right after.

Which tool was only used against the following extensions: 100, 101, 102, 103, and 111?

The question is a tad vague and is assuming — since we now know the SIPvicious suite was used — that we also know to provide the name of the Python script in SIPvicious that was used. There are five tools:

The svcrash tool is something defenders can use to help curtail scanner activity. We can cross that off the list. The svreport tool is for working with data generated by svmap, svwar and/or svcrack. One more crossed off. We also know that the attacker scanned the SIP network looking for nodes, which means svmap and svwar are likely not exclusive tool to the target extensions. (We technically have enough information right now to answer the question especially if you look carefully at the answer box on the site but that’s cheating).

The SIP request line and header field like “To:” destination information in the form of a SIP URI. Since we only care about the extension component of the URI for this question, we can use a regular expression to isolate them.

Back to the SIP log to see if we can find the identified extensions. We’ll also process the “From:” header just in case we need it.

sip_log_parsed %>% 
  mutate_at(
    vars(request, from, to),
    ~stri_match_first_regex(.x, "sip:([^@]+)@")[,2]
  ) %>% 
  select(request, from, to)
## # A tibble: 4,266 x 3
##    request    from       to        
##    <chr>      <chr>      <chr>     
##  1 100        100        100       
##  2 3428948518 3428948518 3428948518
##  3 1729240413 1729240413 1729240413
##  4 admin      admin      admin     
##  5 info       info       info      
##  6 test       test       test      
##  7 postmaster postmaster postmaster
##  8 sales      sales      sales     
##  9 service    service    service   
## 10 support    support    support   
## # … with 4,256 more rows

That worked! We can now see what friendly-scanner attempted to authenticate only to our targets:

sip_log_parsed %>%
  mutate_at(
    vars(request, from, to),
    ~stri_match_first_regex(.x, "sip:([^@]+)@")[,2]
  ) %>% 
  filter(
    user_agent == "friendly-scanner",
    stri_detect_fixed(contents, "Authorization")
  ) %>% 
  distinct(to)
## # A tibble: 4 x 1
##   to   
##   <chr>
## 1 102  
## 2 103  
## 3 101  
## 4 111

While we’re missing 100 that’s likely due to it not requiring authentication (svcrack will REGISTER first to determine if a target requires authentication and not send cracking requests if it doesn’t).

Which extension on the honeypot does NOT require authentication?

We know this due to what we found in the previous question. Extension 100 does not require authentication.

How many extensions were scanned in total?

We just need to count the distinct to’s where the user agent is the scanner:

sip_log_parsed %>% 
  mutate_at(
    vars(request, from, to),
    ~stri_match_first_regex(.x, "sip:([^@]+)@")[,2]
  ) %>% 
  filter(
    user_agent == "friendly-scanner"
  ) %>% 
  distinct(to)
## # A tibble: 2,652 x 1
##    to        
##    <chr>     
##  1 100       
##  2 3428948518
##  3 1729240413
##  4 admin     
##  5 info      
##  6 test      
##  7 postmaster
##  8 sales     
##  9 service   
## 10 support   
## # … with 2,642 more rows

There is a trace for a real SIP client. What is the corresponding user-agent? (two words, once space in between)

We only need to look for user agent’s that aren’t our scanner:

sip_log_parsed %>% 
  filter(
    user_agent != "friendly-scanner"
  ) %>% 
  count(user_agent)
## # A tibble: 1 x 2
##   user_agent          n
##   <chr>           <int>
## 1 Zoiper rev.6751    14

Multiple real-world phone numbers were dialed. Provide the first 11 digits of the number dialed from extension 101?

Calls are “INVITE” requests

sip_log_parsed %>% 
  mutate_at(
    vars(from, to),
    ~stri_match_first_regex(.x, "sip:([^@]+)@")[,2]
  ) %>% 
  filter(
    from == 101,
    stri_detect_regex(cseq, "INVITE")
  ) %>% 
  select(to) 
## # A tibble: 3 x 1
##   to              
##   <chr>           
## 1 900114382089XXXX
## 2 00112322228XXXX 
## 3 00112524021XXXX

The challenge answer box provides hint to what number they want. I’m not sure but I suspect it may be randomized, so you’ll have to match the pattern they expect with the correct digits above.

What are the default credentials used in the attempted basic authentication? (format is username:password)

This question wants us to look at the HTTP requests that require authentication. We can get he credentials info from the zeek$http log:

zeek$http %>% 
  distinct(username, password)
## # A tibble: 2 x 2
##   username password
##   <chr>    <chr>   
## 1 <NA>     <NA>    
## 2 maint    password

Which codec does the RTP stream use? (3 words, 2 spaces in between)

“Codec” refers to the algorithm used to encode/decode an audio or video stream. The RTP RFC uses the term “payload type” to refer to this during exchanges and even has a link to RFC 3551 which provides further information on these encodings.

The summary packet table that tshark generates helpfully provides summary info for RTP packets and part of that info is PT=… which indicates the payload type.

packets %>% 
  filter(proto == "RTP") %>% 
  select(info)
## # A tibble: 2,988 x 1
##    info                                                       
##    <chr>                                                      
##  1 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6402, Time=126160
##  2 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6403, Time=126320
##  3 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6404, Time=126480
##  4 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6405, Time=126640
##  5 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6406, Time=126800
##  6 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6407, Time=126960
##  7 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6408, Time=127120
##  8 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6409, Time=127280
##  9 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6410, Time=127440
## 10 PT=ITU-T G.711 PCMU, SSRC=0xA254E017, Seq=6411, Time=127600
## # … with 2,978 more rows

How long is the sampling time (in milliseconds)?

  • 1 Hz = 1,000 ms
  • 1 ms = 1,000 Hz

(1/8000) * 1000

What was the password for the account with username 555?

We don’t really need to use external programs for this but it will sure go quite a bit faster if we do. While the original reference page for sipdump and sipcrack is defunct, you can visit that link to go to the Wayback machine’s capture of it. It will help if you have a linux system handy (so Docker to the rescue for macOS and Windows folks) since the following answer details are running on Ubunbu.

This question is taking advantage of the fact that the default authentication method for SIP is extremely weak. The process uses an MD5 challenge/response, and if an attacker can capture call traffic it is possible to brute force the password offline (which is what we’ll use sipcrack for).

You can install them via sudo apt install sipcrack.

We’ll first generate a dump of the authentication attempts with sipdump:

system("sipdump -p src/Voip-trace.pcap sip.dump", intern=TRUE)
##  [1] ""                                                               
##  [2] "SIPdump 0.2 "                                                   
##  [3] "---------------------------------------"                        
##  [4] ""                                                               
##  [5] "* Using pcap file 'src/Voip-trace.pcap' for sniffing"           
##  [6] "* Starting to sniff with packet filter 'tcp or udp'"            
##  [7] ""                                                               
##  [8] "* Dumped login from 172.25.105.40 -> 172.25.105.3 (User: '555')"
##  [9] "* Dumped login from 172.25.105.40 -> 172.25.105.3 (User: '555')"
## [10] "* Dumped login from 172.25.105.40 -> 172.25.105.3 (User: '555')"
## [11] ""                                                               
## [12] "* Exiting, sniffed 3 logins"

cat(readLines("sip.dump"), sep="\n")
## 172.25.105.3"172.25.105.40"555"asterisk"REGISTER"sip:172.25.105.40"4787f7ce""""MD5"1ac95ce17e1f0230751cf1fd3d278320
## 172.25.105.3"172.25.105.40"555"asterisk"INVITE"sip:1000@172.25.105.40"70fbfdae""""MD5"aa533f6efa2b2abac675c1ee6cbde327
## 172.25.105.3"172.25.105.40"555"asterisk"BYE"sip:1000@172.25.105.40"70fbfdae""""MD5"0b306e9db1f819dd824acf3227b60e07

It saves the IPs, caller, authentication realm, method, nonce and hash which will all be fed into the sipcrack.

We know from the placeholder answer text that the “password” is 4 characters, and this is the land of telephony, so we can make an assumption that it is really 4 digits. sipcrack needs a file of passwords to try, so We’ll let R make a randomized file of 4 digit pins for us:

cat(sprintf("%04d", sample(0:9999)), file = "4-digits", sep="\n")

We only have authenticaton packets for 555 so we can automate what would normally be an interactive process:

cat(system('echo "1" | sipcrack -w 4-digits sip.dump', intern=TRUE), sep="\n")
## 
## SIPcrack 0.2 
## ----------------------------------------
## 
## * Found Accounts:
## 
## Num  Server      Client      User    Hash|Password
## 
## 1    172.25.105.3    172.25.105.40   555 1ac95ce17e1f0230751cf1fd3d278320
## 2    172.25.105.3    172.25.105.40   555 aa533f6efa2b2abac675c1ee6cbde327
## 3    172.25.105.3    172.25.105.40   555 0b306e9db1f819dd824acf3227b60e07
## 
## * Select which entry to crack (1 - 3): 
## * Generating static MD5 hash... c3e0f1664fde9fbc75a7cbd341877875
## * Loaded wordlist: '4-digits'
## * Starting bruteforce against user '555' (MD5: '1ac95ce17e1f0230751cf1fd3d278320')
## * Tried 8904 passwords in 0 seconds
## 
## * Found password: '1234'
## * Updating dump file 'sip.dump'... done

Which RTP packet header field can be used to reorder out of sync RTP packets in the correct sequence?

Just reading involved here: 5.1 RTP Fixed Header Fields.

The trace includes a secret hidden message. Can you hear it?

We could command line this one but honestly Wireshark has a pretty keen audio player. Fire it up, open up the PCAP, go to the “Telephony” menu, pick SIP and play the streams.