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Audit History

ml-engineer - 5 audits

Version comparison

Capability and finding changes across audited versions, newest first.

Version	Date	Result	Change vs previous
v5 Latest	Aug 4, 2026, 02:27 PM	No confirmed findings	No capability change
v4	Jul 7, 2026, 12:59 AM	No confirmed findings	No capability change
v3	Jul 7, 2026, 12:59 AM	No confirmed findings	No capability change
v2	Jun 30, 2026, 04:21 PM	No confirmed findings	External commands
v1	Feb 25, 2026, 10:19 AM	No confirmed findings	Baseline

Audit version 5 Latest

Aug 4, 2026, 02:27 PM

Both static findings are false positives caused by ordinary Markdown prose. The skill contains no executable shell command, system reconnaissance behavior, or semantic evidence of malicious intent.

Files scanned

172

Lines analyzed

Review items

False positives ignored

Risk Factors

⚙️ External commands (1)

SKILL.md:24

Audited by: codex

Audit version 4

Jul 7, 2026, 12:59 AM

The two static findings are false positives. The first is a markdown reference to a resource file, and the second is a recommendation systems capability statement. No prompt injection, exfiltration intent, or unsafe execution behavior was found in SKILL.md.

Files scanned

169

Lines analyzed

Review items

False positives ignored

Risk Factors

⚙️ External commands (1)

SKILL.md:26

Audited by: codex

Audit version 3

Jul 7, 2026, 12:59 AM

Files scanned

169

Lines analyzed

Review items

False positives ignored

Risk Factors

⚙️ External commands (1)

SKILL.md:26

Audited by: codex

Audit version 2

Jun 30, 2026, 04:21 PM

Static analysis reported one external command pattern, four weak cryptography patterns, and one system reconnaissance pattern in SKILL.md. Review found these are false positives caused by Markdown backticks and machine learning terminology, not executable code or malicious behavior. No prompt injection, data exfiltration, or hidden execution intent was found.

Files scanned

169

Lines analyzed

Review items

False positives ignored

Static false positives ignored (6)

These static matches were dismissed by semantic review or matched schema-only tokens, so they are shown for transparency but do not drive the quality score.

Low

SKILL.md:26

False Positive: Markdown Resource Reference

The static analyzer flagged line 26 as Ruby or shell backtick execution. The line only uses Markdown backticks around resources/implementation-playbook.md and instructs the assistant to open a local reference if examples are needed.

The backticks delimit a Markdown file path, not executable syntax. No shell command, interpreter invocation, or dynamic user input is present.

Low

SKILL.md:3

False Positive: Weak Cryptography Pattern

The static analyzer flagged line 3 as weak cryptography. The line is part of the skill description for production machine learning systems and contains no cryptographic API or algorithm use.

The surrounding frontmatter describes ML frameworks. No evidence found of MD5, SHA-1, DES, RC4, or other weak cryptographic implementation.

Low

SKILL.md:152

False Positive: Weak Cryptography Pattern

The static analyzer flagged line 152 as weak cryptography. The line describes ML system architecture design and does not reference cryptographic operations.

The context is the response approach for designing ML systems. No encryption, hashing, key handling, or weak algorithm usage appears on this line.

Low

SKILL.md:161

False Positive: Weak Cryptography Pattern

The static analyzer flagged line 161 as weak cryptography. The line is an example prompt about a recommendation system and has no cryptographic content.

The phrase concerns model serving scale for recommendations. No evidence found of a cryptographic primitive or insecure implementation.

Low

SKILL.md:165

False Positive: Weak Cryptography Pattern

The static analyzer flagged line 165 as weak cryptography. The line is an example prompt about model monitoring and drift detection.

The content is ordinary MLOps terminology. No evidence found of cryptographic code, secret handling, or algorithm selection.

Low

SKILL.md:111

False Positive: System Reconnaissance Pattern

The static analyzer flagged line 111 as system reconnaissance. The line lists recommendation systems as an ML application area and does not inspect the host environment.

The word systems appears in a machine learning taxonomy. No evidence found of host enumeration, operating system probing, or environment discovery.

Risk Factors

⚙️ External commands (1)

SKILL.md:26

Audited by: codex

Audit version 1

Feb 25, 2026, 10:19 AM

Prompt-only skill with no executable code. Static analysis found 0 files with executable content and computed risk score of 0/100. The SKILL.md file contains only markdown documentation and AI assistant instructions for ML engineering tasks. No security concerns identified.

Files scanned

Lines analyzed

Review items

False positives ignored

No confirmed security findings were recorded for this completed audit.

Audited by: claude

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