github-evidence-kit

name	github-evidence-kit
description	Generate, export, load, and verify forensic evidence from GitHub sources. Use when creating verifiable evidence objects from GitHub API, GH Archive, Wayback Machine, local git repositories, or security vendor reports. Handles evidence storage, querying, and re-verification against original sources.
version	2
author	mbrg
tags	["github","forensics","osint","evidence","verification","git"]

GH Evidence Kit

Purpose: Create, store, and verify forensic evidence from GitHub-related public sources and local git repositories.

When to Use This Skill

• Creating verifiable evidence objects from GitHub activity
• Local git forensics - analyzing cloned repositories, dangling commits, reflog
• Exporting evidence collections to JSON for sharing/archival
• Loading and re-verifying previously collected evidence
• Recovering deleted GitHub content (issues, PRs, commits) from GH Archive
• Tracking IOCs (Indicators of Compromise) with source verification

Quick Start

from src.collectors import GitHubAPICollector, LocalGitCollector, GHArchiveCollector
from src import EvidenceStore

# Create collectors for different sources
github = GitHubAPICollector()
local = LocalGitCollector("/path/to/repo")
archive = GHArchiveCollector()

# Collect evidence from GitHub API
commit = github.collect_commit("aws", "aws-toolkit-vscode", "678851b...")
pr = github.collect_pull_request("aws", "aws-toolkit-vscode", 7710)

# Collect evidence from local git (first-class forensic source)
local_commit = local.collect_commit("HEAD")
dangling = local.collect_dangling_commits()  # Forensic gold!

# Store and export
store = EvidenceStore()
store.add(commit)
store.add(pr)
store.add(local_commit)
store.add_all(dangling)
store.save("evidence.json")

# Verify all evidence against original sources
is_valid, errors = store.verify_all()

Collectors

GitHubAPICollector

Collects evidence from the live GitHub API.

from src.collectors import GitHubAPICollector

collector = GitHubAPICollector()

Method	Returns
collect_commit(owner, repo, sha)	CommitObservation
collect_issue(owner, repo, number)	IssueObservation
collect_pull_request(owner, repo, number)	IssueObservation
collect_file(owner, repo, path, ref)	FileObservation
collect_branch(owner, repo, branch_name)	BranchObservation
collect_tag(owner, repo, tag_name)	TagObservation
collect_release(owner, repo, tag_name)	ReleaseObservation
collect_forks(owner, repo)	list[ForkObservation]

LocalGitCollector (First-Class Forensics)

Collects evidence from local git repositories. Essential for forensic analysis of cloned repos.

from src.collectors import LocalGitCollector

collector = LocalGitCollector("/path/to/cloned/repo")

# Collect a specific commit
commit = collector.collect_commit("HEAD")
commit = collector.collect_commit("abc123")

# Find dangling commits (not reachable from any ref)
# This is forensic gold - reveals force-pushed or deleted commits!
dangling = collector.collect_dangling_commits()
for commit in dangling:
    print(f"Found dangling: {commit.sha[:8]} - {commit.message}")

Method	Returns
collect_commit(sha)	CommitObservation
collect_dangling_commits()	list[CommitObservation]

GHArchiveCollector

Collects and recovers evidence from GH Archive (BigQuery). Requires credentials.

from src.collectors import GHArchiveCollector

collector = GHArchiveCollector()

# Query events by timestamp (YYYYMMDDHHMM format)
events = collector.collect_events(
    timestamp="202507132037",
    repo="aws/aws-toolkit-vscode"
)

# Recover deleted content
deleted_issue = collector.recover_issue("aws/aws-toolkit-vscode", 123, "2025-07-13T20:30:24Z")
deleted_pr = collector.recover_pr("aws/aws-toolkit-vscode", 7710, "2025-07-13T20:30:24Z")
deleted_commit = collector.recover_commit("aws/aws-toolkit-vscode", "678851b", "2025-07-13T20:30:24Z")
force_pushed = collector.recover_force_push("aws/aws-toolkit-vscode", "2025-07-13T20:30:24Z")

Method	Returns
collect_events(timestamp, repo, actor, event_type)	list[Event]
recover_issue(repo, number, timestamp)	IssueObservation
recover_pr(repo, number, timestamp)	IssueObservation
recover_commit(repo, sha, timestamp)	CommitObservation
recover_force_push(repo, timestamp)	CommitObservation

WaybackCollector

Collects archived snapshots from the Wayback Machine.

from src.collectors import WaybackCollector

collector = WaybackCollector()

# Get all snapshots for a URL
snapshots = collector.collect_snapshots("https://github.com/owner/repo")

# With date filtering
snapshots = collector.collect_snapshots(
    "https://github.com/owner/repo",
    from_date="20250101",
    to_date="20250731"
)

# Fetch actual content of a snapshot
content = collector.collect_snapshot_content(
    "https://github.com/owner/repo",
    "20250713203024"  # YYYYMMDDHHMMSS format
)

Verification

Verification is separated from data collection. Use ConsistencyVerifier to validate evidence against original sources.

from src.verifiers import ConsistencyVerifier

verifier = ConsistencyVerifier()

# Verify single evidence
result = verifier.verify(commit)
if not result.is_valid:
    print(f"Errors: {result.errors}")

# Verify multiple
result = verifier.verify_all([commit, pr, issue])

Or use the convenience method on EvidenceStore:

store = EvidenceStore()
store.add_all([commit, pr, issue])
is_valid, errors = store.verify_all()

EvidenceStore

Store, query, and export evidence collections.

from src import EvidenceStore
from datetime import datetime

store = EvidenceStore()

# Add evidence
store.add(commit)
store.add_all([pr, issue, ioc])

# Query
commits = store.filter(observation_type="commit")
recent = store.filter(after=datetime(2025, 7, 1))
from_github = store.filter(source="github")
from_git = store.filter(source="git")
repo_events = store.filter(repo="aws/aws-toolkit-vscode")

# Export/Import
store.save("evidence.json")
store = EvidenceStore.load("evidence.json")

# Summary
print(store.summary())
# {'total': 5, 'events': {...}, 'observations': {...}, 'by_source': {...}}

# Verify all against sources
is_valid, errors = store.verify_all()

Loading Evidence from JSON

from src import load_evidence_from_json
import json

with open("evidence.json") as f:
    data = json.load(f)

for item in data:
    evidence = load_evidence_from_json(item)
    # Evidence is now a typed Pydantic model

Evidence Types

Events (from GH Archive)

All 12 GitHub event types are supported:

Type	Description
PushEvent	Commits pushed
PullRequestEvent	PR opened/closed/merged
IssueEvent	Issue opened/closed
IssueCommentEvent	Comment on issue/PR
CreateEvent	Branch/tag created
DeleteEvent	Branch/tag deleted
ForkEvent	Repository forked
WatchEvent	Repository starred
MemberEvent	Collaborator added/removed
PublicEvent	Repository made public
ReleaseEvent	Release published/created/deleted
WorkflowRunEvent	GitHub Actions run

Observations (from GitHub API, Local Git, Wayback, Vendors)

Type	Description	Sources
CommitObservation	Commit metadata and files	GitHub, Git, GH Archive
IssueObservation	Issue or PR	GitHub, GH Archive
FileObservation	File content at ref	GitHub
BranchObservation	Branch HEAD	GitHub
TagObservation	Tag target	GitHub
ReleaseObservation	Release metadata	GitHub
ForkObservation	Fork relationship	GitHub
SnapshotObservation	Wayback snapshots	Wayback
IOC	Indicator of Compromise	Vendor
ArticleObservation	Security report/blog	Vendor

IOC Types

from src import EvidenceSource, IOCType
from src.schema import IOC, VerificationInfo
from pydantic import HttpUrl
from datetime import datetime, timezone

# IOCs are created directly as schema objects
ioc = IOC(
    evidence_id="ioc-commit-sha-abc123",
    observed_when=datetime.now(timezone.utc),
    observed_by=EvidenceSource.SECURITY_VENDOR,
    observed_what="Malicious commit SHA found in vendor report",
    verification=VerificationInfo(
        source=EvidenceSource.SECURITY_VENDOR,
        url=HttpUrl("https://vendor.com/report")
    ),
    ioc_type=IOCType.COMMIT_SHA,
    value="678851bbe9776228f55e0460e66a6167ac2a1685",
)

Available IOC types: COMMIT_SHA, FILE_PATH, FILE_HASH, CODE_SNIPPET, EMAIL, USERNAME, REPOSITORY, TAG_NAME, BRANCH_NAME, WORKFLOW_NAME, IP_ADDRESS, DOMAIN, URL, API_KEY, SECRET

Testing

Run Unit Tests

cd .claude/skills/github-forensics/github-evidence-kit
pip install -r requirements.txt
pytest tests/ -v --ignore=tests/test_integration.py

Run Integration Tests (Optional)

Integration tests hit real external services (GitHub API, BigQuery, vendor URLs):

# All integration tests
pytest tests/test_integration.py -v -m integration

# Skip integration tests in CI
pytest tests/ -v -m "not integration"

Note: GitHub API integration tests use 60 req/hr unauthenticated rate limit. BigQuery tests require credentials (see below).

GCP BigQuery Credentials (for GH Archive)

GH Archive queries require Google Cloud BigQuery credentials. Two options:

Option 1: JSON File Path

export GOOGLE_APPLICATION_CREDENTIALS=/path/to/credentials.json

Option 2: JSON Content in Environment Variable

Useful for .env files or CI secrets:

export GOOGLE_APPLICATION_CREDENTIALS='{"type":"service_account","project_id":"...","private_key":"..."}'

The client auto-detects JSON content vs file path.

Setup Steps

1. Create a Google Cloud Project
2. Enable BigQuery API
3. Create a Service Account with BigQuery User role
4. Download JSON credentials
5. Set GOOGLE_APPLICATION_CREDENTIALS env var

Free Tier: 1 TB/month of BigQuery queries included.

Requirements

pip install -r requirements.txt

• pydantic - Schema validation
• requests - HTTP client
• google-cloud-bigquery - GH Archive queries (optional)
• google-auth - GCP authentication (optional)