Git Blame

Security

Production code audit via git blame. Natural language risk analysis — overtime commits, scattered changes, no-PR-review merges, and impact domain tracing for every suspicious line.

Install

openclaw skills install git-blame

Git Blame Auditor

Audit perspective git blame. Not "why does this code exist?" — but "is this code safe?"

You're in a security review. A line catches your eye — exec("rm -rf " + userInput). git blame shows it was pushed on a Saturday at 2 AM by a junior dev, in a 47-file mega-commit with no PR review. Is this an accident? A backdoor? Or just a bad week?

Git Blame Auditor reads the same raw git data as any blame tool, but interprets it through an audit and risk lens. It flags risk signals (⏰ overtime, 📦 scattered change, 🚫 no review, 🔍 indirect invocation), maps impact domains (which tests, services, or endpoints touch this code), and outputs a structured risk verdict.

This skill is explicitly not a history archaeology tool. Use phy-git-blame-archaeologist if you want to reconstruct the narrative timeline and original decision rationale behind a line. Use this skill when you need to assess code safety, risk posture, and author patterns for audits, security reviews, or on-call incident triage.

What This Skill IS (vs IS NOT)

Criterion	Git Blame Auditor (this skill)	phy-git-blame-archaeologist (competitor)
Primary lens	Security & code audit	History archaeology
Question answered	"Is this change risky?"	"Why does this code exist?"
Output	Risk score + author pattern + impact domain	Narrative timeline + decision rationale
Risk signals	⏰ Overtime, 📦 Scattered, 🚫 No review, 🔍 Indirect use	Mystery blocks (terse messages), rename history
Impact analysis	Cross-file call graph / dependency trace	Rename trail
Author profiling	Commit-time patterns, file affinity, area expertise	Basic author attribution
Review signal	Extract PR/commit review status	Message quality classification
Target user	Security auditor, tech lead, on-call engineer	Developer onboarding, code historian
Model	DeepSeek (recommended)	GPT-5.5

Trigger Phrases

"audit this line" / "risk check this change"
"who last touched this and is it safe"
"is this code risky"
"blame audit on" / "git blame audit"
"find suspicious commits in"
"show risky changes by this author"
"/git-blame-audit"

How to Provide Input

# Option 1: Audit a specific line (risk-focused blame)
/git-blame-audit src/payment/gateway.ts:142

# Option 2: Audit a range
/git-blame-audit src/payment/gateway.ts:140-155

# Option 3: Audit a symbol (function / class / constant)
/git-blame-audit --symbol processRefund src/

# Option 4: Full file audit — get risk summary of every line
/git-blame-audit src/payment/gateway.ts

# Option 5: Author risk profile — all risky commits by one person
/git-blame-audit --author "alice@company.com" --since 2026-01-01

# Option 6: Time-window scan — all commits in last 7 days with risk markers
/git-blame-audit --since "7 days ago"

Step 1: Run git blame and collect raw signals

# Get blame for a specific line with full porcelain
git blame -L 142,142 src/payment/gateway.ts --porcelain

# For a range
git blame -L 140,155 src/payment/gateway.ts --porcelain

# For an entire file (condensed)
git blame --date=short src/payment/gateway.ts

Read and extract these fields from porcelain output:

abc1234def5678... 142 142
author Alice Chen
author-mail <alice@company.com>
author-time 1825027200     ← Unix timestamp
author-tz +0800
committer Alice Chen
committer-time 1825027200
summary fix: validate amount
previous e1234567 src/payment/gateway.ts
filename src/payment/gateway.ts
        const MAX_AMOUNT = 100000

Extract for risk assessment:

author-time → convert to local time → flag if outside 09:00-18:00 Mon-Fri
summary → check for PR/issue references in message
previous → know the exact previous commit on this line
Commit hash → use for Step 2 (review status check)

Step 2: Assess review status and commit size

# Get full commit details
COMMIT="abc1234def5678"
git show $COMMIT --stat               # How many files changed?
git log --format="%H%n%an%n%ae%n%ai%n%s%n%b" $COMMIT -1

# Check if it's a merge commit (may indicate no individual review)
git cat-file -p $COMMIT | head -5
# If it shows two parents (Merge: xxx yyy), it's a merge commit

# Count total files changed (scatter metric)
git diff-tree --no-commit-id -r --name-only $COMMIT | wc -l

# Count total lines changed (churn metric)
git diff --stat $COMMIT | tail -1 | grep -oP '\d+ insertions?'
git diff --stat $COMMIT | tail -1 | grep -oP '\d+ deletions?'

Risk thresholds (configurable):

🔴 High scatter: > 15 files changed in one commit
🟡 Medium scatter: 8-15 files changed
⏰ Overtime: commit timestamp outside standard working hours (configurable: default Mon-Fri 09:00-18:00)
🚫 No PR reference: commit message lacks PR/issue pattern (#\d+, PR-\d+, JIRA-\d+)
📏 Large churn: > 500 lines added or deleted

Step 3: Impact domain analysis — what depends on this code?

# Find functions / classes that reference this symbol
# If the blamed line defines a symbol:
git grep -n "processRefund\|MAX_AMOUNT" -- src/ -- ':!*.test.*'

# Find all callers within the codebase
# (Use grep to find function invocations)
git grep -n "processRefund(" -- src/ -- ':!*.test.*'

# Find ALL files touched by this commit (not just the blamed line)
git diff-tree --no-commit-id -r --name-only $COMMIT | sort

Classify impact domains:

Database / migrations
Payment / billing
Authentication / authorization
Public API endpoints
Internal utilities
Configuration / constants
Build / CI
Test files (lower risk per line but may indicate testing gaps)

Step 4: Author pattern analysis

# Author's recent commit count
git shortlog -sn --since="2026-01-01" --until="now" | grep "Alice Chen"

# Author's file affinity — what areas does this author normally touch?
git log --author="alice@company.com" --oneline --name-only --since="2026-01-01" \
  | grep -E "\.(ts|js|py|go|java|rb)$" | sort | uniq -c | sort -rn | head -10

# Author's commit time distribution
git log --author="alice@company.com" --format="%ai" --since="2026-01-01" \
  | cut -d' ' -f2 | cut -d: -f1 | sort | uniq -c | sort -rn

# Does the author normally work in this area?
# If their top 10 files never include this module → ⚠️ out-of-area change

Author risk signals:

🔄 Out-of-area: Author normally works in frontend, but this change is in database migrations
🌙 Night pattern: > 40% of commits outside 09:00-18:00
🆕 New contributor: Author has < 10 commits in this repository
📈 Churn spike: This month's commit count is > 3× their monthly average
🗂️ Wide scatter: Author's last commit touched files across 5+ unrelated modules

Step 5: Composite risk scoring

Combine risk signals into a weighted score (0-100):

Signal	Weight	Detection
Overtime commit	+15	timestamp outside working hours
Scattered commit (15+ files)	+20	git diff-tree wide footprint
No PR/issue reference	+15	commit message lacks `#\d+`, `PR-`
Out-of-area change	+15	author's file affinity doesn't include this module
Large churn (500+ lines)	+10	diff stat large
Merge commit (no individual review)	+10	commit has 2+ parents
Night owl author pattern	+10	>40% commits at night
New contributor (<10 commits)	+10	shortlog count low
Indirect/high-risk function	+15	calls `exec`, `eval`, `fs.write`, SQL raw, crypto
Delicate domain	+15	touches payment, auth, data migration

Risk bands:

🟢 LOW (0-20): Routine change, reviewed, in-area, normal hours
🟡 MEDIUM (21-50): Some flags — worth a second look during review
🟠 HIGH (51-75): Multiple risk signals — audit before deployment
🔴 CRITICAL (76-100): Strong risk pattern — immediate investigation

Step 6: Output structured risk report

## Git Blame Audit Report
**Target**: `src/payment/gateway.ts:142` — `const MAX_AMOUNT = 100000`

---

### 🔴 Risk Score: 72 / 100 (HIGH)

| Risk Factor | Weight | Details |
|---|---|---|
| ⏰ Overtime | +15 | Sat 2026-06-13 02:15 CST |
| 📦 Scattered | +20 | 47 files changed |
| 🚫 No review | +15 | Merge commit, no PR/issue reference |
| 🔍 Out-of-area | +10 | Author's main area: frontend/src |
| 🆕 New contributor | +10 | Only 4 total commits |
| ⚠️ Delicate domain | +15 | Payment code — affects billing |

---

### 🧑‍💻 Author Profile

**Alice Chen** `<alice@company.com>` (active since 2026-05-20)

- **Total commits in repo**: 4 (all in last 3 weeks)
- **File affinity**: `frontend/src/components/`, `frontend/src/api/`
- **This commit area**: `src/payment/` (first time → out-of-area)
- **Commit time pattern**: 3 of 4 commits after 22:00
- **Typical reviewer**: No review found for any commit

---

### 🌐 Impact Domain

`MAX_AMOUNT = 100000` is used in:

src/payment/processor.ts:47 ← amount check logic src/payment/validation.ts:88 ← input validation src/api/checkout.ts:23 ← POST /checkout endpoint


**Upstream callers** (files calling into these 3 files):

src/controllers/OrderController.ts:15 src/workers/paymentWorker.ts:33


**This change affects**: payment processing, checkout flow, order controller.

---

### 📋 Risk Detail

**The commit `a1b2c3d4` changed 47 files across 6 modules:**

| Module | Files Changed |
|---|---|
| frontend/src/components | 14 |
| frontend/src/api | 8 |
| src/payment | 7 ← new area for author |
| src/db/migrations | 5 ← extremely sensitive |
| src/config | 4 ← production config |
| tests | 9 |

**3 files contain high-risk operations:**
- `src/payment/executeRefund.ts:22` — `eval()` used with dynamic input
- `src/db/migrations/20260613_add_columns.sql` — raw SQL (migration)
- `src/payment/gateway.ts:142` — MAX_AMOUNT cap changed from 50000 → 100000

---

### ✅ Recommendation

1. 🔴 **Hold deployment** — this commit requires manual review
2. 👥 Assign reviewer with payment domain expertise
3. 🔄 Request author to split into focused commits (one concern per commit)
4. 📝 Add issue reference linking to the business requirement for the 2× amount increase
5. 🧪 Verify test coverage for the new MAX_AMOUNT boundary

---

### 📊 Quick Verdict

Git Blame Audit: src/payment/gateway.ts:142 ────────────────────────────────────────────────── Risk: 🔴 HIGH (72/100) Author: Alice Chen (new, out-of-area, night pattern) When: Sat 02:15 — 47 files, 6 modules, no review What: MAX_AMOUNT doubled (50000 → 100000) Impact: Payment processing, checkout, order controller Action: 🛑 Hold. Requires domain expert review.


---

## Quick Mode Output

/git-blame-audit src/config.prod.ts:23

🟠 RISK: 62/100 ⏰ Overtime (Sun 23:47) +10 📦 23 files +15 🚫 No PR ref +15 🔍 Env config +10 🆕 New contributor +12 Author: Bob (2 total commits, no reviews) Change: API_ENDPOINT changed to https://staging.example.com Action: 🛑 Investigate — staging URL in production config


---

## First Success Path

For first-time users, here's the fastest path to a valuable result:

1. **Navigate** to any git repository on your machine
2. **Run**: `/git-blame-audit any-file.ts:10` (pick any file with at least 10 lines)
3. **Verify** you see:
   - A risk score (0-100)
   - At least one risk marker (overtime, scattered, etc.)
   - The author and commit context
4. **Optionally drill deeper**: `/git-blame-audit --author "$(git log --format='%ae' -1)" --since 2026-01-01`

Expected time: < 30 seconds from trigger to first report.

---

## Sample Prompts

- "Audit `src/api/users.ts:88` — is this change safe?"
- "Show me all risky commits from Alice in the last 30 days"
- "Flag every line in `src/payment/` that was committed outside business hours"
- "Risk check the last 10 commits on the `main` branch"
- "Who changed `MAX_RETRIES` and is it a concern?"
- "Find all lines in `src/db/` that lack a PR reference in blame"
- "This PR touches 4 unrelated modules — audit the risk score"
- "Compare risk patterns between Alice and Bob's commits this sprint"

---

## Notes

- **Works fully offline** — only requires local git binary and the repository
- **No external API calls** — all analysis is local
- **Model**: DeepSeek recommended for the natural language risk interpretation
- **Configurable thresholds**: Risk thresholds can be adjusted per team policy
- **Not a replacement for code review** — it's a triage tool to focus reviewer attention
- **PR reference patterns** are currently tuned for GitHub (`#\d+`) and Jira (`[A-Z]+-\d+`); extendable in config