SKILLEMALL.ai
GitHub ↗ RU Sign in

CC performing-cloud-native-forensics-with-falco

Uses Falco YAML rules for runtime threat detection in containers and Kubernetes, monitoring syscalls for shell spawns, file tampering, network anomalies, and privilege escalation. Manages Falco rules via the Falco gRPC API and parses Falco alert output. Use when building container runtime security or investigating k8s cluster compromises.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 444 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Uses Falco YAML rules for runtime threat detection in containers and Kubernetes, monitoring syscalls for shell spawns, file tampering, network anomalies, and…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

AnalyzerKubernetesSecurityPeople and hiringAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Dangerous commands cmd-privilege scripts/agent.py:49
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      "desc": "Detect setuid/setgid calls in container",
      detectorcode literal
    • low Dangerous commands cmd-privilege scripts/agent.py:50
      Privilege escalation / world-writable permissions (detector / deny-list definition; string literal in code, not executed)
      "condition": "evt.type in (setuid, setgid) and container "
      detectorcode literal
    • low Risky intent intent-offensive-security SKILL.md:5
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      and privilege escalation. Manages Falco rules via the Falco gRPC API and parses
    • low Dangerous commands cmd-privilege SKILL.md:77
      Privilege escalation / world-writable permissions (documentation of a security skill)
      4. Privilege escalation via setuid/setgid
      security skill
    • low Risky intent intent-offensive-security SKILL.md:77
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      4. Privilege escalation via setuid/setgid

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 51/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 444 tokens

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 340: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.