Targets multiple TFMs via polyfills and conditional compilation. PolySharp, API compat.
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概要と使いどころ
Targets multiple TFMs via polyfills and conditional compilation. PolySharp, API compat.
日本語の概要は準備中です。原文の説明を表示しています。
Build a minimal context pack and recommend the correct specialist path for token-efficient execution. Use when the task is non-trivial, spans multiple domains, or should reduce token usage before implementation.
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Create or update active planning documents under `planning/active`, then define the execution slices, validations, specialist handoff, and closeout expectations. Use when the task is non-trivial, multi-step, or explicitly asks for planning.
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Use as the single visible starter and controller for workspace work that may change files, runtime assets, planning state, docs, settings, or governance. Normalize the request into the Super Agent lifecycle: intake, spec registration for non-trivial work, planning registration, specialist routing, execution, testing, review, closeout, and planning-state updates before implementation begins.
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Use for non-trivial, design-bearing, or architecture-affecting work before execution planning. Creates or updates a versioned spec under planning/specs/active/ with design intent, alternatives, risks, and acceptance criteria.
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Use for non-trivial feature, behavior, workflow, or architecture work before execution planning. Create or update a versioned spec under planning/specs/active with design intent, alternatives, risks, acceptance criteria, and planning readiness.
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Execute a trivial task inline — no subagents, no planning overhead
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Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.
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Exploit Kerberos Constrained Delegation misconfigurations in Active Directory to impersonate privileged users via S4U2self and S4U2proxy extensions for lateral movement and privilege escalation.
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Detect Living Off the Land Binaries (LOLBins/LOLBAS) abuse including certutil, regsvr32, mshta, and rundll32 via process telemetry, Sigma rules, and parent-child process analysis
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Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.
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Detect DCSync attacks where adversaries abuse Active Directory replication privileges to extract password hashes by monitoring for non-domain-controller accounts requesting directory replication via DsGetNCChanges.
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Detect anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.
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Detect compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.
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Detect command injection attacks against Modbus TCP/RTU protocol in ICS environments by monitoring for unauthorized write operations, anomalous function codes, malformed frames, and deviations from established communication baselines using ICS-aware IDS and protocol deep packet inspection.
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Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.
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Detect malicious scheduled task creation and modification using Sysmon Event IDs 1 (Process Create for schtasks.exe), 11 (File Create for task XML), and Windows Security Event 4698/4702. The analyst correlates task creation with suspicious parent processes, public directory paths, and encoded command arguments to identify persistence and lateral movement via scheduled tasks. Activates for requests involving scheduled task detection, Sysmon persistence hunting, or T1053.005 Scheduled Task/Job analysis.
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Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.
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Deploys canary files (honeytokens) across file systems to detect ransomware encryption activity in real time. Uses strategically placed decoy documents monitored via file integrity monitoring or OS-level watchdogs to trigger alerts when ransomware modifies or encrypts them. Activates for requests involving ransomware canary deployment, honeyfile setup, deception-based ransomware detection, or file integrity monitoring for encryption.
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Deploys and monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption begins.
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This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.
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Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.
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Detect unauthorized modifications to running containers by monitoring for binary execution drift, file system changes, and configuration deviations from the original container image.
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Parses Software Bill of Materials (SBOM) in CycloneDX and SPDX JSON formats to identify supply chain vulnerabilities by correlating components against the NVD CVE database via the NVD 2.0 API. Builds dependency graphs, calculates risk scores, identifies transitive vulnerability paths, and generates compliance reports. Activates for requests involving SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation.
日本語の概要は準備中です。原文の説明を表示しています。