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api-server-sent-events

Server-Sent Events (SSE / EventSource) exploitation — origin abuse for cross-site streaming exfil, prompt-injection via SSE messages into LLM clients, retry-after token leak, fragmenting events to bypass content-type sniffers.

69

Quality

85%

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SecuritybySnyk

Critical

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SKILL.md
Quality
Evals
Security

Quality

Content

87%

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

A concise, highly actionable SSE attack reference with executable examples and clean organization; the main gap is workflow clarity, since it presents bug classes as a catalog without explicit verification checkpoints.

Suggestions

Add a short ordered testing workflow (e.g., 1. confirm text/event-stream, 2. probe each bug class, 3. verify impact) with an explicit validation/check step per class to lift workflow_clarity.

For the reconnection and prompt-injection classes, include a verify step (e.g., confirm the token appears in proxy logs, confirm the injected marker reaches the client) so results are checked rather than assumed.

DimensionReasoningScore

Conciseness

The body is lean and almost entirely actionable (curl probes, Python sseclient, HTML PoC, payload samples); the single-line SSE intro is minimal context rather than padding, so every section earns its place.

3 / 3

Actionability

It provides fully executable, copy-paste-ready commands and code (curl -N, sseclient loop, attacker EventSource snippet, injected JSON payloads) rather than vague direction.

3 / 3

Workflow Clarity

The Detect section gives an initial sequence and the bug classes are enumerated, but it reads as a catalog of attack classes without explicit validation checkpoints or a verify→fix→retry loop, so the sequence present lacks checkpoints.

2 / 3

Progressive Disclosure

Content is organized into clear single-level sections (Detect, Top bug classes, Tooling, OPSEC, References) with external references listed flatly and no nested/deep references, so navigation is easy.

3 / 3

Total

11

/

12

Passed

Description

82%

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 specific, well-scoped offensive-security description with concrete actions and good trigger terms, weakened only by the absence of an explicit 'Use when' clause. Adding trigger guidance would lift the completeness dimension.

Suggestions

Append an explicit trigger clause such as 'Use when testing SSE / EventSource endpoints, cross-origin streaming, or LLM streaming-token clients' to satisfy the 'when' half of completeness.

Mirror the broader when_to_use keywords (text/event-stream, retry, Last-Event-ID) into the description so trigger coverage is not split across fields.

DimensionReasoningScore

Specificity

The description lists several concrete actions ('origin abuse for cross-site streaming exfil, prompt-injection via SSE messages into LLM clients, retry-after token leak, fragmenting events to bypass content-type sniffers'), matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

It clearly answers 'what' (SSE exploitation across named bug classes) but contains no 'Use when...' clause or equivalent explicit trigger guidance, so per the rubric guideline completeness is capped at 2.

2 / 3

Trigger Term Quality

It opens with natural terms a user would say — 'Server-Sent Events (SSE / EventSource)' — giving good coverage of the common phrasings rather than only technical jargon.

3 / 3

Distinctiveness Conflict Risk

The SSE-exploitation niche is sharply scoped with distinct triggers, making it unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
PurpleAILAB/Decepticon
Reviewed

Table of Contents

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