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0xD8C4A475/liberated-mjpeg

An AI-generated MJPEG decoder, liberated from human-written code. Benchmarked against FFmpeg. The robots did their best.

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  • ★ 0
  • commit efd1458f1a40
  • scored 2026-11-14
  • scoring prov-5+qual-2+sec-2

unreviewed-ai-risk

AI provenance

100%

explicit

Confidence
71%
Coverage
100%

Estimated share of AI-generated code. Explicit attribution is a lower bound.

Code quality

54/100

weak

Confidence
90%
Coverage
100%

Complexity, duplication, lint density, tests, CI, docs and review process.

Security

65/100

weak

Confidence
85%
Coverage
100%

Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.

AI provenance

100% explicit

Explicit AI attribution on 100% of first-party code added; an estimated 100% including velocity signals.

How the score is built

  • Explicitly attributed share100%
  • Unattributed share in AI-pace bursts0%
  • Estimated AI-generated share100%
  • AI tool configuration files0
  • Work sessions at AI pace0
  • Releases at AI pacenot measured
  • Coding-style index (1.0+ means possible)3.29

Attributed AI tools

ToolCommitsLines addedFirst seenLast seen
Claude Code25,3382026-03-132026-03-13

Lines added per month all AI-attributed share

  1. 2026-035,338 · 100% AI

Findings in AI-attributed lines vs the rest

From git blame: 4,257 lines trace to AI-attributed commits, 0 to others. Too few lines in one group for a fair comparison. Reported, not scored.

Findings per 1,000 linesAI-attributedOtherRatio
Code quality1.18——
Security4.23——

Evidence by analyzer

Explicit AI attributionok3 items
attributed_commit_share
66.7%
attributed_commits
2
attributed_loc
5,338
attributed_loc_share
100.0%
commits
3
effective_loc
5,338
tools_detected
1
AI tool configurationok
artifacts
0
tools_configured
0
workflow_agents
0
Commit velocityok
excluded_import_loc
4,292
flagged_loc
0
flagged_loc_share
0.0%
flagged_units
0
max_loc_per_hour
261.50
measured_loc
1,046
median_loc_per_hour
261.50
pr_timed_units
0
pre_ai_era_burst_loc
0
pre_ai_era_bursts
0
pre_ai_era_measured_loc
0
work_units
1
Release velocityskipped
Coding styleok8 items
count:assistant_voice
0
count:emoji_in_code
0
count:narrated_steps
14
count:placeholder
0
files:assistant_voice
0
files:emoji_in_code
0
files:narrated_steps
3
files:placeholder
0
index
3.29
lines_scanned
4,257
per_kloc:assistant_voice
0
per_kloc:emoji_in_code
0
per_kloc:narrated_steps
3.29
per_kloc:placeholder
0
Findings in AI-written linesok
ai_lines
4,257
blame_failures
0
files_blamed
28
other_lines
0
quality:ai_findings
5
quality:ai_per_kloc
1.18
quality:other_findings
0
security:ai_findings
18
security:ai_per_kloc
4.23
security:other_findings
0

Code quality

54 weak

Code quality is weak: test-to-source ratio 0.25, no CI test run detected; 40% of function code in complex or long functions; 3% duplicated lines. Weakest area: complexity.

How the score is built

  • Complexity30
  • Duplication85
  • Lint and smells75
  • Tests and CI43
  • Documentation65
  • Type safety40
  • Review processnot measured

Evidence by analyzer

Complexity (lizard)ok9 items
complex_functions
8
function_nloc
2,361
functions
94
long_functions
4
many_param_functions
0
mean_ccn
6.39
p90_ccn
12
risky_nloc_share
40.4%
Duplication (jscpd)ok4 items
compared_lines
2,914
duplicated_lines
78
duplicated_share
2.7%
files
28
Lintok
category:best-practice
4
category:correctness
1
findings
5
scanned_lines
4,257
weighted_findings
5
Tests and CIok
check:ci_present
no
check:ci_runs_lint
no
check:ci_runs_tests
no
check:has_tests
yes
check:test_ratio
no
check:tests_cochange
yes
ci_files
0
cochange_commits
2
cochange_share
50.0%
source_lines
4,257
test_lines
1,069
test_ratio
0.25
Documentationok2 items
  • README.md README.md
  • LICENSE LICENSE
check:changelog
no
check:contributing
no
check:license
yes
check:readme
yes
readme_lines
196
Type safetyok
check:low_escape_density
yes
check:strict_config
no
escapes
0
escapes_per_kloc
0

Security

65 weak

Security posture is weak: 6 high-severity SAST findings. Weakest area: posture.

How the score is built

  • Secrets100
  • Static analysis (SAST)54
  • Vulnerable dependenciesnot measured
  • CI workflowsnot measured
  • Security posture0
  • OpenSSF Scorecardnot measured

Evidence by analyzer

OpenSSF Scorecardskipped

no published OpenSSF Scorecard result for this repo

Package registriesskipped

no registry dependencies declared

Secrets (gitleaks)ok
secrets_current
0
secrets_history
0
secrets_low_confidence
0
secrets_nonprod
0
Static analysis (opengrep)ok
findings
18
findings_high
6
findings_low
0
findings_medium
12
parse_errors
0
scanned_lines
4,257
weighted_findings
7.50
Dependencies (osv-scanner)skipped
CI workflows (zizmor)skipped
Security postureok
check:dependency_updates
no
check:lockfiles
yes
check:security_policy
no
check:signed_commits
no
signed_commit_share
33.3%
unpinned_manifests
0
Release downloadsok
binary_assets
0
signals
0
suspicious
0

Findings

6 high17 medium

SeverityRuleLocationMessageTool
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit scripts/benchmark.py:111 Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... Static analysis (opengrep)
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit scripts/benchmark.py:52 Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... Static analysis (opengrep)
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit scripts/benchmark.py:70 Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... Static analysis (opengrep)
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit scripts/validate_quality.py:40 Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... Static analysis (opengrep)
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit scripts/validate_quality.py:72 Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... Static analysis (opengrep)
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit scripts/validate_quality.py:89 Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external... Static analysis (opengrep)
medium opengrep/python.lang.best-practice.unspecified-open-encoding bench_plot.py:12 Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding="utf-8"). Lint
medium opengrep/python.lang.best-practice.unspecified-open-encoding scripts/benchmark.py:388 Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding="utf-8"). Lint
medium opengrep/python.lang.best-practice.unspecified-open-encoding scripts/generate_charts.py:19 Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding="utf-8"). Lint
medium opengrep/python.lang.best-practice.unspecified-open-encoding scripts/validate_quality.py:314 Missing 'encoding' parameter. 'open()' uses device locale encodings by default, corrupting files with special characters. Specify the encoding to ensure cross-platform support when opening files in text mode (e.g. encoding="utf-8"). Lint
medium opengrep/c.lang.correctness.incorrect-use-ato-fn tools/cmj_bench.c:326 Avoid the 'ato*()' family of functions. Their use can lead to undefined behavior, integer overflows, and lack of appropriate error handling. Instead prefer the 'strtol*()' family of functions. Lint
medium opengrep/c.lang.security.insecure-use-memset src/huffman.c:21 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/huffman_fast.c:18 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_decoder.c:134 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_decoder.c:151 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_decoder.c:64 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_decoder.c:65 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_decoder.c:66 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_decoder.c:67 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset src/jpeg_parser.c:270 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset tools/cmj_bench.c:114 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset tools/cmj_bench.c:169 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)
medium opengrep/c.lang.security.insecure-use-memset tools/cmj_decode.c:105 When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While `memset()` is commonly used for this purpose, it can leave sensitive information... Static analysis (opengrep)

Tools and coverage

Every analyzer that ran on this commit. A failed or skipped tool is a coverage gap: its share of the score is left out and the coverage figure drops.

AnalyzerPillarStatusVersionFindingsNote
AI tool configurationAI provenanceoksignatures-v10
Explicit AI attributionAI provenanceoksignatures-v10
Release velocityAI provenanceskipped—0
Coding styleAI provenanceok—0
Commit velocityAI provenanceokprov-40
Findings in AI-written linesAI provenanceokgit-blame0
Complexity (lizard)Code qualityoklizard 1.25.10
DocumentationCode qualityok—0
Duplication (jscpd)Code qualityokrepotrust-dup-w60
LintCode qualityokopengrep 1.33.1; rules f1d2b562b4145
Tests and CICode qualityok—0
Type safetyCode qualityok—0
CI workflows (zizmor)Securityskipped—0
Dependencies (osv-scanner)Securityskipped—0
Release downloadsSecurityok—0
Security postureSecurityok—0
Package registriesSecurityskipped—0no registry dependencies declared
Static analysis (opengrep)Securityokopengrep 1.33.1; rules f1d2b562b41418
OpenSSF ScorecardSecurityskipped—0no published OpenSSF Scorecard result for this repo
Secrets (gitleaks)Securityokgitleaks 8.30.10

Score history

Scores from different scoring versions aren't directly comparable.

ScoredCommitScoringAI provenanceQualitySecurity
2026-11-14efd1458f1a40prov-5+qual-2+sec-2100%5465
2026-11-14efd1458f1a40prov-4+qual-2+sec-2100%5465

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Maintainers can show these in a README. Badges update when the repository is re-scored.

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Full text report

Scores

Unreviewed AI code risk: a large share of this code is explicitly AI-attributed, and its tests or review process are weak while quality or security scores are low.

Pillar Score Signal Confidence Coverage
AI provenance (estimated AI-generated share) 100 explicit 71% 100%
Code quality 54 weak 90% 100%
Security 65 weak 85% 100%

AI provenance

Explicit AI attribution on 100% of first-party code added; an estimated 100% including velocity signals.

  • Explicitly attributed share (lower bound): 100.0%
  • Unattributed share in AI-consistent velocity bursts: 0.0%
  • Estimated AI-generated share: 100.0%
AI tool Attributed commits Lines added
Claude Code 2 5,338

Current source lines last changed by AI-attributed commits: 4,257 of 4,257.

Too few lines in one group to compare finding densities.

  • Stylometry index: 3.29 per 1,000 lines (narrated steps 14, placeholders 0, assistant phrasing 0, emoji 0). Reported as a signal, not scored.
Month Lines added Attributed to AI
2026-03 5,338 100%

Evidence

  • Claude Code: trailer 'Co-Authored-By: Claude' (efd1458f1a40)
  • Claude Code: trailer 'Co-Authored-By: Claude' (86570f638e7a)
  • step-by-step narration comment: /* Step 1: Dequantize (coefficients are in zigzag order, output in natural order) */ (src/idct.c:4)
  • step-by-step narration comment: /* Step 2: 2D IDCT */ (src/idct.c:4)
  • step-by-step narration comment: /* Step 3: Level shift (add 128) and clamp */ (src/idct.c:7)
  • step-by-step narration comment: /* Step 1: Dequantize and de-zigzag into workspace (natural order) */ (src/idct_fas)
  • step-by-step narration comment: /* Step 2: 1D IDCT on each row */ (src/idct_fas)
  • step-by-step narration comment: /* Step 3: Transpose so column IDCT becomes row IDCT */ (src/idct_fas)
  • step-by-step narration comment: /* Step 4: 1D IDCT on each column (now rows after transpose) */ (src/idct_fas)
  • step-by-step narration comment: /* Step 5: Transpose back, level shift (+128), and clamp */ (src/idct_fas)

AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.

Code quality

Code quality is weak: test-to-source ratio 0.25, no CI test run detected; 40% of function code in complex or long functions; 3% duplicated lines. Weakest area: complexity.

Area Score
Complexity (lizard) 30
Duplication 85
Code smells (Opengrep) 75
Tests and CI 43
Documentation 65
Type safety 40
Process (Scorecard review/maintenance) n/a
  • Functions: 94; mean complexity 6.4, 90th percentile 12; 8 complex and 4 long functions
  • Duplicated lines: 2.7% of 2,914 compared
  • Tests: 1,069 test lines for 4,257 source lines (ratio 0.25); CI test commands: none detected; 50% of recent source commits also change tests
  • Docs missing or thin: contributing, changelog

Most complex functions:

Security

Security posture is weak: 6 high-severity SAST findings. Weakest area: posture.

Area Score
Secrets (gitleaks, tree + history) 100
Static analysis (Opengrep) 54
Vulnerable dependencies (OSV) n/a
CI workflows (zizmor) n/a
Posture (policy, updates, signing, lockfiles) 0
OpenSSF Scorecard n/a
  • Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits

Top findings

Severity Finding Location
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] scripts/benchmark.py:52
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] scripts/benchmark.py:70
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] scripts/benchmark.py:111
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] scripts/validate_quality.py:40
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] scripts/validate_quality.py:72
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] scripts/validate_quality.py:89
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/huffman.c:21
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/huffman_fast.c:18
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_decoder.c:64
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_decoder.c:65
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_decoder.c:66
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_decoder.c:67
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_decoder.c:134
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_decoder.c:151
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] src/jpeg_parser.c:270
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] tools/cmj_bench.c:114
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] tools/cmj_bench.c:169
medium opengrep/c.lang.security.insecure-use-memset: When handling sensitive information in a buffer, it's important to ensure that the data is securely erased before the buffer is deleted or reused. While memset() is commonly used for this purpose, it can leave sensitive information behind due to compiler optimizations or other factors. To avoi [confidence low] tools/cmj_decode.c:105

Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.

Repository profile

  • Source lines: 4,257; test lines: 1,069
Language Lines
C 4,151
Python 1,038
Shell 137