mirror of https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git synced 2026-06-26 11:44:37 +03:00

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mukul975 8cae0648ec Add 55 new skills across 3 new domains + 6 undercovered areas (762 -> 817)

Demand-driven expansion targeting the fastest-growing 2025-2026 threat and
skills categories (ISC2/WEF/CrowdStrike/Mandiant signals):

- AI Security (NEW domain, 12 skills): LLM red-teaming with garak/PyRIT,
  prompt injection (direct/indirect/RAG), MCP tool-poisoning, agentic tool
  invocation, guardrails, model/data poisoning, system-prompt leakage,
  embedding/vector weaknesses, model extraction, continuous red-teaming
- Supply Chain Security (NEW domain, 5 skills): SBOMs, dependency confusion,
  malicious-npm triage, typosquatting, SLSA/Sigstore provenance
- Hardware & Firmware Security (NEW domain, 4 skills): CHIPSEC/UEFI audit,
  Secure Boot bypass, TPM measured-boot attestation, ESP bootkit hunting
- Identity (10): Entra ID/ROADtools, GraphRunner, AADInternals, ADCS/Certipy,
  shadow credentials, coercion, BloodHound CE, device-code phishing, SSO abuse
- Cloud-native (8): Stratus, Pacu, CloudFox, container escape, K8s RBAC,
  Falco, Trivy, kube-bench
- Offensive C2 (6): Sliver, Havoc, NetExec, DPAPI, NTLM relay ESC8, redirectors
- DFIR (6): Hayabusa, Chainsaw, KAPE, Velociraptor, EZ Tools, Plaso
- Backfill (4): OpenCTI, MISP, honeytokens, post-quantum crypto migration

Each skill follows the repo taxonomy (SKILL.md + references/{standards,api-reference}.md
+ scripts/agent.py + LICENSE), with researched real tool commands (no placeholders),
complete frontmatter, and ATT&CK/ATLAS + NIST CSF mappings. Updates README domain
table, skill count, and index.json.

2026-06-22 19:08:16 +02:00

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API Reference — Agentic AI Tool Invocation Controls

NVIDIA NeMo Guardrails

Install: pip install nemoguardrails

API	Description
`RailsConfig.from_path("./guardrails_config")`	Load rails config (config.yml, prompts.yml, *.co flows)
`RailsConfig.from_content(yaml_content=..., colang_content=...)`	Load config inline
`LLMRails(config)`	Build a guarded LLM wrapper
`rails.generate(messages=[...])`	Run input/output/tool rails around generation
`rails.register_action(fn, name=...)`	Register a custom tool/action under rail control

Built-in flows: self check input, self check output, self check facts. Rail types: input, output, dialog, retrieval, execution/tool.

jsonschema

Install: pip install jsonschema

API	Description
`validate(instance=args, schema=schema)`	Raise `ValidationError` if args violate schema
`additionalProperties: false`	Deny-by-default extra arguments
`pattern` / `maxLength` / `enum`	Constrain argument values (e.g. recipient domain allowlist)

AWS STS (boto3) — scoped identity

Install: pip install boto3

API	Description
`sts.assume_role(RoleArn, RoleSessionName, Policy, DurationSeconds)`	Assume a role with an inline session policy that further restricts permissions
`DurationSeconds=900`	Short-lived (15 min) credentials, least privilege
`boto3.Session(aws_access_key_id=..., aws_session_token=...)`	Use the scoped creds for the tool call

Policy decision contract

Decision	Meaning	Action
`allow`	Allowlisted, args valid, low impact	Execute tool
`require_approval`	High-impact tool	Route to human-in-the-loop, fail-closed
`deny`	Unknown tool or invalid args	Reject and log

External References

NeMo Guardrails docs: https://docs.nvidia.com/nemo/guardrails/
jsonschema docs: https://python-jsonschema.readthedocs.io/
OWASP Agentic AI Top 10: https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/

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