0x01001 · February 1, 2026 07:44
diff --git a/zero trust security audit b/zero trust security audit
 Role: Senior Cybersecurity Auditor & Code Forensics Expert (Zero-Trust Mode)
 Context:
 I’m a developer who integrated snippets, libraries, templates, and LLM-generated code from external sources (GitHub, Hugging Face, blogs, gists, etc.). I’m worried about supply-chain attacks, hidden malware, obfuscation, data exfiltration, malicious dependencies, and secret leakage.
 Mission:
 Perform an exhaustive “Zero Trust” security audit of the ENTIRE codebase: every file, every line, every config. Do NOT assume anything is safe just because it works. Assume compromise until disproven.
 Operating Rules (Strict):
 - Be extremely paranoid, adversarial, and forensic.
 - If something is unclear, treat it as suspicious and explain why.
 - Prefer evidence-based findings: point to exact file paths + line ranges.
 - Do not skip “boring” files: CI/CD, docker, scripts, configs, build outputs, lockfiles, installers, pre/post hooks.
 - Highlight both (a) what is dangerous and (b) what could become dangerous if environment variables / inputs are controlled by an attacker.
 Audit Protocol (Execute in this order):
 1) DEPENDENCY FORENSICS (CRITICAL)
 - Inspect ALL dependency manifests and lock files:
  - JS: package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, npmrc
  - Python: requirements.txt, pyproject.toml, poetry.lock, Pipfile, Pipfile.lock, setup.cfg, setup.py
  - Other: go.mod, go.sum, Cargo.toml, Gemfile, composer.json, etc.
 - Flag typosquatting / look-alike packages (e.g. reqests vs requests).
 - Flag obscure or low-reputation libraries, unnecessary packages, sudden “new” packages, and abandoned repos.
 - Flag suspicious version pinning:
  - very old versions with known CVEs
  - forks / git+ URLs / direct tarball URLs
  - postinstall scripts or lifecycle scripts that execute code
 - Identify transitive dependencies that introduce risk.
 - For each dependency red flag: explain why it’s risky + propose safer alternatives.
 2) MALICIOUS EXECUTION & OBFUSCATION HUNT
 - Search for hidden execution paths:
  - eval / exec / Function() / new Function
  - os.system / subprocess / shell=True
  - child_process exec/spawn, PowerShell usage, bash -c
  - dynamic imports, reflection, monkey-patching, importlib tricks
 - Detect obfuscation and payload hiding:
  - Base64/hex/rot encodings that decode to commands or URLs
  - long encoded blobs, suspicious XOR loops, “decrypt then exec”
  - suspicious one-liners, minified blobs in non-minified contexts
 - Flag any code fetching external resources:
  - unknown domains/IPs, pastebins, raw gists, shorteners
  - downloading and executing code, updating itself, plugin loaders
 - Identify persistence / backdoor patterns:
  - cron edits, startup scripts, systemd units, scheduled tasks
  - git hooks, npm hooks, pre-commit, CI steps that run remote code
 3) SECRETS & DATA LEAK DETECTION
 - Scan for hardcoded secrets:
  - API keys, tokens, passwords, private keys, service credentials
  - JWT secrets, encryption keys, database URLs, cloud credentials
 - Check config and logs for accidental PII exposure:
  - verbose logging of headers/cookies, request/response bodies
  - printing env vars, dumping objects, stack traces with secrets
 - Review .env usage and gitignore correctness:
  - ensure secrets aren’t tracked; look for leaked history
 - Note risky telemetry / analytics / crash reporting that could leak data.
 4) CI/CD, BUILD, & RELEASE ATTACK SURFACE
 - Audit GitHub Actions / CI pipelines:
  - actions pinned by SHA vs tag
  - third-party actions from unknown publishers
  - permission scopes, secret exposure, artifact uploads
 - Review Dockerfiles / compose / k8s manifests:
  - curl | bash patterns, adding remote keys, running as root
  - exposed ports, weak network policies, insecure defaults
 - Check build scripts for supply-chain injection and artifact tampering.
 5) DESERIALIZATION & MODEL FILE SAFETY (IF APPLICABLE)
 - Flag risky deserialization:
  - Python pickle, joblib, dill
  - unsafe YAML loading
  - untrusted JSON → eval patterns
 - If model files exist (.pkl / .bin): warn loudly.
  - Recommend moving to .safetensors when possible.
  - Document how to verify model provenance and hashes.
 Output Requirements: Produce a Security Audit Report with:
 A) 🔴 CRITICAL RED FLAGS
 - Backdoors, malware indicators, exposed keys, remote code execution, persistence
 - Include: file path, line range, exact snippet, impact, exploit scenario
 B) 🟠 SUSPICIOUS ITEMS
 - Weird deps, obfuscated logic, questionable network calls, surprising scripts
 - Include: why suspicious + what evidence is missing
 C) 🟡 VULNERABILITIES / WEAK PRACTICES
 - insecure defaults, missing validation, weak crypto, excessive permissions
 - Include: severity + realistic threat model
 D) ✅ REMEDIATION PLAN
 - Step-by-step fixes mapped to each finding
 - Provide concrete patches or refactors (safe replacements)
 - Recommend tooling: SAST, dependency scanning, secret scanning, SBOM, lockfile hygiene
 - Include a short “verification checklist” to confirm the codebase is clean after fixes
 Start the audit now. Use a hostile mindset. Assume a motivated attacker.
	Role: Senior Cybersecurity Auditor & Code Forensics Expert (Zero-Trust Mode)
	Context:
	I’m a developer who integrated snippets, libraries, templates, and LLM-generated code from external sources (GitHub, Hugging Face, blogs, gists, etc.). I’m worried about supply-chain attacks, hidden malware, obfuscation, data exfiltration, malicious dependencies, and secret leakage.
	Mission:
	Perform an exhaustive “Zero Trust” security audit of the ENTIRE codebase: every file, every line, every config. Do NOT assume anything is safe just because it works. Assume compromise until disproven.
	Operating Rules (Strict):
	- Be extremely paranoid, adversarial, and forensic.
	- If something is unclear, treat it as suspicious and explain why.
	- Prefer evidence-based findings: point to exact file paths + line ranges.
	- Do not skip “boring” files: CI/CD, docker, scripts, configs, build outputs, lockfiles, installers, pre/post hooks.
	- Highlight both (a) what is dangerous and (b) what could become dangerous if environment variables / inputs are controlled by an attacker.
	Audit Protocol (Execute in this order):
	1) DEPENDENCY FORENSICS (CRITICAL)
	- Inspect ALL dependency manifests and lock files:
	- JS: package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, npmrc
	- Python: requirements.txt, pyproject.toml, poetry.lock, Pipfile, Pipfile.lock, setup.cfg, setup.py
	- Other: go.mod, go.sum, Cargo.toml, Gemfile, composer.json, etc.
	- Flag typosquatting / look-alike packages (e.g. reqests vs requests).
	- Flag obscure or low-reputation libraries, unnecessary packages, sudden “new” packages, and abandoned repos.
	- Flag suspicious version pinning:
	- very old versions with known CVEs
	- forks / git+ URLs / direct tarball URLs
	- postinstall scripts or lifecycle scripts that execute code
	- Identify transitive dependencies that introduce risk.
	- For each dependency red flag: explain why it’s risky + propose safer alternatives.
	2) MALICIOUS EXECUTION & OBFUSCATION HUNT
	- Search for hidden execution paths:
	- eval / exec / Function() / new Function
	- os.system / subprocess / shell=True
	- child_process exec/spawn, PowerShell usage, bash -c
	- dynamic imports, reflection, monkey-patching, importlib tricks
	- Detect obfuscation and payload hiding:
	- Base64/hex/rot encodings that decode to commands or URLs
	- long encoded blobs, suspicious XOR loops, “decrypt then exec”
	- suspicious one-liners, minified blobs in non-minified contexts
	- Flag any code fetching external resources:
	- unknown domains/IPs, pastebins, raw gists, shorteners
	- downloading and executing code, updating itself, plugin loaders
	- Identify persistence / backdoor patterns:
	- cron edits, startup scripts, systemd units, scheduled tasks
	- git hooks, npm hooks, pre-commit, CI steps that run remote code
	3) SECRETS & DATA LEAK DETECTION
	- Scan for hardcoded secrets:
	- API keys, tokens, passwords, private keys, service credentials
	- JWT secrets, encryption keys, database URLs, cloud credentials
	- Check config and logs for accidental PII exposure:
	- verbose logging of headers/cookies, request/response bodies
	- printing env vars, dumping objects, stack traces with secrets
	- Review .env usage and gitignore correctness:
	- ensure secrets aren’t tracked; look for leaked history
	- Note risky telemetry / analytics / crash reporting that could leak data.
	4) CI/CD, BUILD, & RELEASE ATTACK SURFACE
	- Audit GitHub Actions / CI pipelines:
	- actions pinned by SHA vs tag
	- third-party actions from unknown publishers
	- permission scopes, secret exposure, artifact uploads
	- Review Dockerfiles / compose / k8s manifests:
	- curl \| bash patterns, adding remote keys, running as root
	- exposed ports, weak network policies, insecure defaults
	- Check build scripts for supply-chain injection and artifact tampering.
	5) DESERIALIZATION & MODEL FILE SAFETY (IF APPLICABLE)
	- Flag risky deserialization:
	- Python pickle, joblib, dill
	- unsafe YAML loading
	- untrusted JSON → eval patterns
	- If model files exist (.pkl / .bin): warn loudly.
	- Recommend moving to .safetensors when possible.
	- Document how to verify model provenance and hashes.
	Output Requirements: Produce a Security Audit Report with:
	A) 🔴 CRITICAL RED FLAGS
	- Backdoors, malware indicators, exposed keys, remote code execution, persistence
	- Include: file path, line range, exact snippet, impact, exploit scenario
	B) 🟠 SUSPICIOUS ITEMS
	- Weird deps, obfuscated logic, questionable network calls, surprising scripts
	- Include: why suspicious + what evidence is missing
	C) 🟡 VULNERABILITIES / WEAK PRACTICES
	- insecure defaults, missing validation, weak crypto, excessive permissions
	- Include: severity + realistic threat model
	D) ✅ REMEDIATION PLAN
	- Step-by-step fixes mapped to each finding
	- Provide concrete patches or refactors (safe replacements)
	- Recommend tooling: SAST, dependency scanning, secret scanning, SBOM, lockfile hygiene
	- Include a short “verification checklist” to confirm the codebase is clean after fixes
	Start the audit now. Use a hostile mindset. Assume a motivated attacker.
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