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BB exploiting-broken-function-level-authorization

Tests APIs for Broken Function Level Authorization (OWASP API5:2023) by identifying admin and privileged endpoints, then reaching them with regular-user credentials via HTTP method switching, URL path manipulation, and parameter tampering. Use when testing whether low-privilege users can invoke admin API functions or otherwise escalate privileges via function-level access control gaps.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 3 843 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Tests APIs for Broken Function Level Authorization (OWASP API5:2023) by identifying admin and privileged endpoints, then reaching them with regular-user…

As a process B 69/100 · Nearly there — weak spots: running it twice, progress reporting

ProcedureSecuritytype 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
B
90/100
safety, quality, tests
Safety 60%
96
Quality 40%
82
Run on models
none yet
Process rating
B
69/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
When it triggers w 12
50
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Risky intent intent-offensive-security references/api-reference.md:15
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | Vertical privilege escalation | User accessing admin endpoints |
    • low Risky intent intent-offensive-security SKILL.md:38
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Assessing APIs for vertical privilege escalation where users can invoke functions above their role
    • low Risky intent intent-offensive-security SKILL.md:198
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      ### Step 4: Parameter-Based Privilege Escalation
    • low Risky intent intent-offensive-security SKILL.md:302
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      | **Vertical Privilege Escalation** | Accessing functions or data restricted to a higher privilege level, such as regular user accessing admin endpoints |

    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"
    • note edit-residue the text marks something as outdated (lines 233): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 69/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 30 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3843 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
    • -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
    • +4Description says when NOT to use the skill
    • +3Description length 388: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 30 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.