Results for “detection”

Deploy honeytokens and canarytokens as decoy artifacts to detect intrusions with near-zero false positives.

Transform threat intelligence and attack patterns into testable hunting hypotheses for proactive threat detection.

Review local branch changes for bugs, security vulnerabilities, and code quality issues using a structured checklist-driven process.

Detect business email compromise (BEC) attacks using email gateway rules, behavioral analytics, and financial process controls.

Scan Kubernetes resource manifests with Kubesec to identify misconfigurations, privilege escalation risks, and deviations from security best practices.

Detect and triage infrastructure drift by comparing declared Terraform state against live cloud resources using scheduled pipelines and audit logs.

Executes a structured ransomware incident response from initial detection through containment, forensic analysis, decryption assessment, recovery, and post-incident hardening.

Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics.

Proactively hunt for adversary abuse of legitimate system binaries (LOLBins) to execute malicious payloads while evading detection.

Detect and extract hidden data embedded in images, audio, and other media files using steganalysis tools to uncover covert communication channels.

Deploys canary files, honeypot shares, and decoy systems to detect ransomware activity at the earliest possible stage.

Analyze AWS GuardDuty findings, detectors, suppression rules, and member accounts with parallel execution and anti-hallucination guardrails.

Scan container images, IaC, and SBOMs for vulnerabilities and misconfigurations in CI/CD with Trivy.

Hunt for Mimikatz execution using command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.

Access 31 pay-per-use tools for quantum security, agent safety, research, data, and earn on Base, paid via x402 protocol.

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing.

Detects anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems using Zeek, Suricata, and custom Python analysis.

Detect process hollowing (T1055.012) by analyzing memory-mapped sections, hollowed process indicators, and parent-child process anomalies in EDR telemetry.

Identifies and unpacks UPX-packed and other packed malware samples to expose the original executable code for static analysis.

Capture and analyze network traffic using Wireshark and tshark to reconstruct network events, extract artifacts, and identify malicious communications.

Automated security auditing covering SAST, DAST, dependency scanning, secret detection, container hardening, and compliance checks before deployments or when integrating new dependencies.

Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness, providing detailed improvement recommendations with frameworks, testing methodologies, and educational content.

Detects and prevents code injection attacks targeting serverless functions through static analysis, event source poisoning detection, and IAM policy auditing.

Analyze suspected malware through static, dynamic, and behavioral techniques, including IOC extraction, YARA or Sigma rules, sandboxing, and anti-analysis behavior detection.

Orchestrates a dimensional-analysis pipeline to annotate codebases with unit/dimension comments, discover dimensional vocabulary, and detect arithmetic bugs from unit mismatches or precision loss.

Deploy a Velociraptor server and agents, then write and execute VQL hunts across a fleet of endpoints for threat hunting and incident response.

Detect and prevent API enumeration attacks including BOLA and IDOR exploitation by monitoring sequential identifier access patterns and authorization failures.

Scan files, directories, and memory dumps using YARA rules to identify malware families, suspicious patterns, and IOC matches.

Detect container escape attempts in real-time using Falco runtime security rules that monitor syscalls, file access, and privilege escalation.

Implement eBPF-based runtime security observability and enforcement in Kubernetes clusters using Cilium Tetragon for kernel-level threat detection and policy enforcement.

Automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.

Configure GitHub Advanced Security with CodeQL to perform automated static analysis and vulnerability detection across repositories at enterprise scale.

Scans Python and JavaScript codebases for bugs, security vulnerabilities, code smells, and anti-patterns, producing a prioritized fix list with line numbers, severity ratings, and suggested corrections.

Analyze a repository to generate recommended Claude Code settings.json permissions for read-only commands, detecting tech stack, build tools, and monorepo structure.

Perform forensic on-chain analysis of EVM tokens to detect scams, rug pulls, and soft rugs by cross-referencing on-chain state against team narratives.

Analyze Windows memory dumps for signs of compromise using the Rekall memory forensics framework, including process injection, hidden processes, and rootkit detection.