CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

agentic-app-audit

Black-box security audit of a DEPLOYED AI agent (not the MCP server behind it) — tool-call hijacking, cross-session memory poisoning, confused-deputy via connected tools, agent-to-agent IDOR, excessive agency / unconfirmed destructive actions, and privilege compromise where the agent holds broader perms than the user. Use when the target is a live assistant/agent product with tool access (bookings, email, payments, file/RAG, browsing) rather than a raw LLM chat box or an MCP server you can read.

72

Quality

91%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tightly written, operationally dense audit playbook: it routes signals to specific attack classes, gives deterministic confirmation oracles to prevent false positives, and stays lean throughout. The main gaps are the absence of concrete probe templates for the excessive-agency and privilege-compromise classes and an implicit rather than explicit end-to-end workflow order.

Suggestions

Add a one-line concrete probe example to §2.5 (excessive agency), e.g. a sample instruction that attempts to trigger a send/pay/delete without the confirmation prompt, mirroring the injection payload shown in §2.1.

Add a brief explicit sequencing line (e.g. 'recon tool surface → apply routing table → run attack class → confirm per §4 → record turn sequence') so the end-to-end audit order is stated, not just implied by section order.

In §2.6, name one concrete enumeration technique (e.g. asking the agent to list its available tools or probing a tool name that should be out of role) to match the specificity of §2.2's oracle.

DimensionReasoningScore

Conciseness

The body is lean with no padding — it never explains concepts Claude already knows, and every section carries operational signal (kill rules, a signal-to-move routing table, concrete oracles). The one-line blockquote earns its place by orienting the core attack philosophy (making the agent *do* vs. *say*).

5 / 5

Actionability

Mostly executable guidance: the routing table maps each signal to a specific move, §2.2 gives a deterministic three-step canary oracle ('remember: FLAG=<canary>', identity switch, re-read), and §2.1 includes a concrete injection payload plus an OOB listener path. It falls short of 5 because §2.5 (excessive agency) and §2.6 (privilege compromise) give direction ('Drive a destructive/irreversible action', 'Enumerate what tools exist, then invoke one') without a concrete probe example.

4 / 5

Workflow Clarity

The Quick Kill Checklist plus routing table give a clear decision flow, and §4 supplies explicit validation (deterministic oracles, two identities, recorded turn sequences), so the destructive-operation validation cap does not apply. It is a 4 rather than 5 because the end-to-end sequence (recon → attack selection → confirmation → reporting) is implied by section order rather than explicitly sequenced as a workflow.

4 / 5

Progressive Disclosure

No bundle files exist, and the body is a compact, well-sectioned overview that points to the authoritative ASI table in `skills/llm-redteam/SKILL.md` instead of duplicating it ('Do not re-define it here'). References are one level deep, clearly signaled, and nothing that belongs in a separate file is inlined.

5 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it names the concrete attack classes, defines a clear niche, and includes an explicit 'Use when...' clause with both positive triggers and exclusion criteria that separate it from sibling skills. The only gap is a few missing natural synonyms (e.g. 'prompt injection', 'red team') that users might say.

DimensionReasoningScore

Specificity

It enumerates six concrete attack techniques — 'tool-call hijacking, cross-session memory poisoning, confused-deputy via connected tools, agent-to-agent IDOR, excessive agency / unconfirmed destructive actions, and privilege compromise' — with scope qualifiers ('black-box', 'DEPLOYED', 'agent holds broader perms than the user'). Comprehensive coverage of the domain, matching anchor 5 rather than 4, whose coverage has minor gaps.

5 / 5

Completeness

Explicitly answers both: what ('Black-box security audit of a DEPLOYED AI agent — [six attack classes]') and when ('Use when the target is a live assistant/agent product with tool access... rather than a raw LLM chat box or an MCP server you can read'), with concrete trigger phrases and explicit exclusion criteria.

5 / 5

Trigger Term Quality

Good natural keyword coverage — 'security audit', 'AI agent', 'MCP server', 'tool access', 'bookings, email, payments', 'LLM chat box' — phrases a user running this audit would naturally say. Not 5 because common synonyms like 'prompt injection', 'red team', or 'pentest' are absent; not 3 because coverage is far better than 'some relevant keywords'.

4 / 5

Distinctiveness Conflict Risk

It actively disambiguates from its two nearest siblings — 'not the MCP server behind it' and 'rather than... an MCP server you can read' — carving a clear niche (deployed-agent black-box audit) with minimal conflict risk. Anchor 5, not 4, since overlap risk is addressed explicitly rather than just being minor.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Awarexone/Agentic-Bug-Hunter

Path

skills/agentic-app-audit/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.