Results for “payload”

Security payloads, bypass tables, wordlists, gf pattern names, always-rejected bug list, and conditionally-valid-with-chain table. Use when you need specific payloads for XSS/SSRF/SQLi/XXE/NoSQLi/command injection/SSTI/IDOR/path-traversal/HTTP smuggling/WebSocket/MFA bypass, or bypass techniques. Submittability and the always-rejected / what-NOT-to-submit decision are owned by triage-validation.

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WAF bypass techniques checklist: encoding bypass (URL/HTML/Unicode/double encoding), case variation, comment injection, HTTP header manipulation, chunked encoding, IP rotation, timing attacks, and payload obfuscation per WAF vendor. Use when WAF is blocking payloads during web app tests.

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Create and update OpenClaw end-to-end tests in Docker, checking complete workflows. Use fake servers to verify requests and real providers to check service behavior, including image understanding and the final text users receive.

• Adding or updating Docker end-to-end tests
• Checking payloads sent to dependencies
• Verifying behavior with real model providers

Read and update application settings through APIs, including system prompts, reasoning limits, IP filters, and login requirements. Also manage proxy and cache settings, with guidance on how reasoning settings affect requests sent to AI providers.

• Review and update system prompts
• Adjust reasoning request settings
• Manage IP filters and login requirements

Review forms, API requests, and browser storage to find personal data that no active feature needs. Identify unnecessary collection, suggest removal or anonymisation, and check analytics and logs for exposed personal identifiers and missing retention periods.

• Reviewing personal data collected by forms
• Finding personal identifiers in analytics and logs
• Reviewing browser storage and retention periods

Review AI skills and bundles without running their code. Checks for data leaks, suspicious permissions, hidden code, and system changes across desktop and mobile platforms, then reports flagged actions, risk scores, and suggested mitigations.

• Review an AI skill before installing it
• Check a skill bundle for data leaks and suspicious actions
• Inspect Android and iOS threats in skill files

Store and retrieve execution output, model responses, reports, and operation receipts in YYLO Ledger. Choose storage and retention settings, attach provenance describing the source, and verify immutable evidence using record identifiers and content digests.

• Preserving test reports and execution output
• Recording AI responses with their source information
• Storing operational plans and contracts as evidence

Trace how requests become rendered pages in a CTF sandbox. Compare display restrictions with server enforcement, inspect data passed to the browser, and preserve a minimal example that demonstrates where rendering behavior diverges.

• Trace routes through server rendering
• Inspect page data passed to the browser
• Compare display restrictions with handler enforcement

Solve sandboxed CTF security challenges by reconstructing encoding and encryption steps, extracting data hidden in media, and tracing mobile app signing or storage behavior. Preserve exact parameters and evidence to reproduce decoded content or signed requests.

• Reconstructing encoding and encryption chains in CTF challenges
• Extracting data hidden in images and other media
• Tracing APK or IPA request-signing logic

Organize authorized bug bounty investigations from scope review through reconnaissance, asset discovery, vulnerability testing, and reporting. Use vulnerability-specific guides to prioritize checks and prepare reproducible findings with evidence, impact, and remediation advice.

• Review a bug bounty program's scope and testing rules
• Gather public information and discover target assets
• Plan API authorization and business logic checks

Analyze DNS logs to find signs of hidden data transfers. Use query length, character randomness, traffic volume, and response sizes to identify suspicious domains and support monitoring rules with Python, Suricata, and Splunk examples.

• Investigating possible data theft through DNS traffic
• Ranking suspicious domains found in DNS logs
• Creating DNS tunneling detection rules

Investigate Windows malware that runs in memory or abuses legitimate system tools. Use logs, registry entries, and memory dumps to trace persistence, identify suspicious activity, and produce detection rules and an analysis report.

• Investigating suspicious PowerShell activity
• Checking WMI persistence mechanisms
• Finding malicious code in memory dumps

Plan authorized spearphishing simulations, personalized phishing tests aimed at specific people. Prepare scenarios and email infrastructure, track delivery and participant responses, and document findings to assess email security controls and improve security awareness.

• Designing authorized phishing simulations for specific personnel
• Preparing test email delivery infrastructure
• Measuring delivery, opens, clicks, and reporting behavior

Screen AI application inputs and historical logs for prompt injection, where malicious instructions try to redirect the model. Combine pattern matching, text structure scoring, and a DeBERTa classifier to flag suspicious content and produce JSON results.

• Screening chatbot and AI agent inputs
• Checking external text used in retrieval-based AI applications
• Auditing historical interaction logs for injection attempts

Analyze Windows PowerShell event logs to reconstruct scripts split across records and identify encoded commands, suspicious downloads, and security scanning bypass attempts. Produce a report with recovered scripts, risk scores, and mappings to documented attack techniques.

• Investigating suspicious PowerShell activity
• Reconstructing scripts split across log records
• Finding encoded commands and suspicious downloads

Inspect suspicious PDFs without opening them in a reader. Use PDFiD, pdf-parser, and peepdf to examine internal objects, extract scripts, embedded files, and URLs, and document how the suspected attack works.

• Triage suspicious PDF email attachments
• Investigate embedded JavaScript and automatic actions
• Extract embedded files and external URLs

Search Windows PowerShell logs for traces of Empire, a framework used after a system is compromised. Identify characteristic launch commands, encoded code, module calls, and communication paths, then report suspicious events with timelines and severity scores.

• Investigating suspected Empire activity
• Checking encoded commands and communication paths
• Building detection rules from Empire indicators

Research malware families through Malpedia, connecting aliases, associated threat groups, and relationships between malware that loads other malware. Collect YARA rules, patterns used to identify malware, and organize references to support investigations and detection work.

• Resolving different vendor names for the same malware
• Mapping malware associated with a threat group
• Documenting chains in which malware loads other malware

Examine suspicious Word, Excel, and PowerPoint documents by extracting macros and untangling code designed to hide its purpose. Identify download addresses, execution triggers, and attack steps, then document findings and indicators for detecting related threats.

• Investigating suspicious email attachments
• Finding download addresses hidden in VBA code
• Examining legacy Excel 4.0 macros

Analyze malware network captures to investigate command-and-control traffic, data theft, and downloaded files. Use packet analysis tools to identify suspicious destinations and recurring connections, extract artifacts, and create detection rules from observed patterns.

• Analyzing malware sandbox network captures
• Investigating command-and-control traffic
• Tracing data theft and file downloads

Create fillable Word forms with text fields, date controls, dropdowns, and clickable checkboxes. Protect static document content while leaving designated fields editable, or prepare mail-merge placeholders for templates that receive data later.

• Creating protected employee onboarding forms
• Building surveys with dropdowns and checkboxes
• Preparing contract templates with editable fields

Refresh installed NanoClaw channel and agent provider code from its registry branches. Update all integrations or a selected subset, check a structured result report, and validate the updated installation with builds and tests.

• Refreshing integrations after a NanoClaw update
• Updating selected channels or agent providers
• Updating from a fork with an upstream remote

Plan a Claude Managed Agent around one clear job, then route work through setup, launch preparation, evaluation, and scheduling. Produce execution plans and curl commands that users run with their own Anthropic API key.

• Defining one clear job for a managed agent
• Preparing launch commands for an Anthropic account
• Planning evaluation and revision with an iteration limit

Prepare a graded Claude Managed Agent for recurring schedules, event triggers, or on-demand use. Validate timing, build deployment request data, optionally include self-evaluation for each run, and document the next steps in a roadmap.

• Schedule an agent to run every morning or weekly
• Prepare a curl trigger for an external event
• Add self-evaluation to each recurring run