[project]
name = "my-project"
path = "/path/to/target"
languages = ["c", "cpp", "python"]The [scanner.performance] section controls incremental scanning and which optional analysis phases run. Each phase flag defaults to a safe value; side-effect-heavy phases (auto-patching, PoC compilation) are opt-in.
[scanner.performance]
# Skip unchanged files based on SHA256 hash comparison (hashes persisted to output dir)
enable_incremental_scan = false
# Maximum number of parallel tasks for scanning operations
max_parallel_tasks = 4
# Enable LLM response caching to avoid redundant API calls
enable_llm_cache = false
# Enable file filtering to reduce false positives
enable_file_filtering = true
# --- Phase enable flags ---
# Each flag controls whether a specific analysis phase runs during the scan.
# Threat modeling using STRIDE analysis (adds LLM-based threat identification)
enable_threat_modeling = true
# Root-cause deduplication (collapses findings that share the same root cause)
enable_root_cause_dedup = true
# Multi-verifier cross-checking (runs additional LLM verification passes)
enable_multi_verifier = true
# Auto-patching (generates and validates fix patches in a staging worktree)
# Writes code files and runs git commands — opt-in for safety
enable_auto_patching = false
# PoC compilation (compiles proof-of-concept exploits to verify findings)
# Spawns external compilers — opt-in for safety
enable_poc_compilation = false
# Confidence refinement (re-calibrates finding confidence based on multi-source/cross-file signals)
enable_confidence_refinement = true
# CVE bootstrap (enriches findings with CVE data from external sources)
enable_cve_bootstrap = true
# Variant search (searches for variant instances of the same vulnerability pattern)
enable_variant_search = true| Flag | Default | Side effects |
|---|---|---|
enable_threat_modeling |
true |
None (read-only analysis) |
enable_root_cause_dedup |
true |
None |
enable_multi_verifier |
true |
Additional LLM API calls |
enable_auto_patching |
false |
Writes code files, runs git commands in a staging worktree |
enable_poc_compilation |
false |
Spawns external compilers |
enable_confidence_refinement |
true |
None |
enable_cve_bootstrap |
true |
External network requests to NVD/CISA |
enable_variant_search |
true |
Additional LLM API calls |
See docs/architecture.md for the full 20-phase pipeline description.
BACO supports single or multiple models per phase. When multiple models are configured, they are used in round-robin fashion to distribute load across different models/providers.
Detailed error logging: When LLM requests fail, BACO reports the HTTP status code, error type (timeout, connection, request, body, decode), and the actual URL for easier debugging.
Single model:
[llm.phases.discovery]
base_url = "https://api.mistral.ai/v1"
api_key = "${MISTRAL_API_KEY}" # or set env var
model = "mistral-small"Multiple models:
[llm.phases.discovery]
base_url = "https://api.mistral.ai/v1"
api_key = "${MISTRAL_API_KEY}"
# 'models' takes precedence over 'model' if both are present
models = ["mistral-small", "mistral-medium", "codestral-latest"]
[llm.phases.verification]
base_url = "https://api.qwen.ai/v1"
api_key = "${QWEN_API_KEY}"
model = "qwen35" # single model
[llm.phases.aggregation]
base_url = "https://api.openai.com/v1"
api_key = "${OPENAI_API_KEY}"
models = ["gpt-4o", "gpt-4o-mini"] # multiple models for distributed loadNote: The models array takes precedence over model if both are present. Models are selected in round-robin fashion to distribute load across different providers.
BACO has two distinct agent modes:
When enabled, the LLM Discovery phase reads source files directly before analyzing findings:
[agent]
enabled = true
max_turns = 10 # Max conversation turns with tools
tool_timeout_secs = 60 # Timeout for tool execution
keep_artifacts = false # Keep generated test filesBenefits:
- LLM reads actual source code before enriching findings
- Uses tools (file_read, pattern_search) for deeper analysis
- Provides more accurate vulnerability descriptions with context
A separate verification phase that uses an embedded security agent with tools to prove or disprove findings:
- file_read: Examine vulnerable code in context
- pattern_search: Look for related vulnerability patterns
- file_write: Create proof-of-concept test cases
- run_test: Execute tests to verify exploitability
The agent automatically removes false positives when tests pass, reducing noise in the final report. This phase runs after LLM Verification and before Ticket Cross-Reference.
BACO uses prompt templates for each phase loaded from markdown files at runtime. You can override these via configuration:
Default prompts are stored in prompts/phases/ as markdown files:
prompts/phases/indexing.mdprompts/phases/semgrep.mdprompts/phases/llm_static_analysis.mdprompts/phases/llm_discovery.mdprompts/phases/llm_verification.mdprompts/phases/ticket_crossref.mdprompts/phases/git_analysis.mdprompts/phases/cross_file_analysis.mdprompts/phases/confidence_scoring.mdprompts/phases/ai_aggregation.mdprompts/phases/reporting.md
View the full prompt templates on GitHub to understand default behavior.
Inline override in config.toml:
[llm.phases.prompt_overrides.phases]
llm_static_analysis = """Analyze this %%LANGUAGE%% code for security vulnerabilities.
Focus on: memory safety, injection risks, and insecure API usage.
File: %%FILE_PATH%%
Code:
%%CODE_CONTENT%%
"""
llm_discovery = """Given this finding, determine if it's a true vulnerability:
Title: %%FINDING_TITLE%%
Location: %%FILE_PATH%%:%%LINE_NUMBER%%
Description: %%VULNERABILITY_DESCRIPTION%%
"""Available template variables:
%%PROJECT_PATH%%- Target project path%%FILE_EXTENSIONS%%- Detected file extensions%%LANGUAGES%%- Target languages%%CODE_CONTENT%%- Code snippet being analyzed%%LANGUAGE%%- Programming language of the file%%FILE_PATH%%- File path%%LINE_RANGE%%- Line numbers%%FINDING_TITLE%%- Vulnerability title%%VULNERABILITY_DESCRIPTION%%- Description text%%FINDINGS_COUNT%%- Total findings count%%SCAN_DATE%%- Scan date
Prompts are validated (max 10,000 characters, no null bytes) before use.
[[tickets.systems]]
type = "github"
url = "https://api.github.com"
credentials.token = "${GITHUB_TOKEN}"- findings.json: Complete vulnerability data with all 16 fields
- report.html: Visual report with severity colors, code snippets, AI summary
- report.sarif: SARIF format for CI/CD integration