Results for “bot”

Deploy and tune Web Application Firewall rules on AWS WAF, Azure WAF, and Cloudflare to protect cloud-hosted applications against OWASP Top 10 attacks, including managed rule sets, custom rate limiting, bot management, and false positive reduction.

Store, retrieve, and automatically rotate credentials, API keys, and other secrets using AWS Secrets Manager.

Administer OpenMetadata platform including users, teams, bots, roles, policies, and security. Use when managing access control, configuring SSO, creating service accounts, setting up team hierarchies, or troubleshooting authentication issues.

Use to design and audit how customers are told they are interacting with AI, or that AI was involved in a decision about them, and to evidence that it happened. Trigger for "do we tell customers it's a bot", "AI disclosure requirements", "should the bot say it's not human", "customer asked if they were talking to a person", AI transparency obligations, or evidencing that an AI-assisted decision was explained.

Set up and manage AWS Cognito user pools, identity pools, OAuth flows, and user authentication with CLI commands and Python SDK examples.

Set up Cloudflare Turnstile end-to-end: create a widget, deploy a managed siteverify Worker, insert frontend snippets, and validate the integration.

Investigate AWS account compromises by querying CloudTrail logs to reconstruct attacker activity, identify compromised credentials, and analyze API call patterns.

Audits a codebase for scalability bottlenecks, flagging N+1 queries, missing indexes, unbounded result sets, blocking operations, and memory pressure, then outputs a prioritized fix list.

Manage AWS Identity and Access Management for users, roles, policies, and permissions. Create IAM policies, configure cross-account access, set up service roles, troubleshoot permission errors, and enforce least-privilege security.

Recovers malware configuration, decodes C2 and beacon parameters, unpacks staged payloads, and extracts bot or campaign IDs from samples in a CTF sandbox environment.

Configure Hardware Security Modules (HSMs) using the PKCS#11 standard interface for key generation, signing, encryption, and key management with both physical HSMs and SoftHSM2 for development.

Monitors cloud workloads for runtime threats by checking process lists, network connections, file integrity, and resource utilization anomalies on EC2 and GCE instances.

Detect and exploit JavaScript prototype pollution vulnerabilities on both client-side and server-side applications to achieve XSS, RCE, and authentication bypass through property injection.

Performs STRIDE-A threat model analysis of repositories and systems, producing architecture overviews, DFD diagrams, prioritized findings, and executive assessments. Supports both single analysis and incremental updates with change tracking.

Apply bottom-up and top-down role mining techniques to discover optimal RBAC roles from existing user-permission assignments, reducing role explosion and enforcing least privilege.

Perform forensic acquisition and analysis of cloud storage services including Google Drive, OneDrive, Dropbox, and Box by collecting both API-based remote data and local sync client artifacts from endpoint devices.

Hunt for threats in AWS environments using Detective behavior graphs, entity investigation timelines, GuardDuty finding correlation, and automated entity profiling across IAM users, EC2 instances, and IP addresses.

Guides the audit of Records of Processing Activities (RoPA) against GDPR Article 30 requirements for both controllers and processors. Activate when verifying RoPA completeness, validating mandatory fields, or preparing for supervisory authority inspections. Keywords: RoPA, Article 30, records audit, processing activities, controller records, processor records.

Runs a structured security audit across six phases: attack-surface mapping, STRIDE/PASTA threat modeling, technical checklists, red/blue team exercises, and a final verdict, covering code, infrastructure, APIs, bots, payments, AI agents, and compliance.

Use to compare a support data retention policy against what is actually still stored, and find both over-retention and premature deletion. Trigger for "are we deleting support data on time", "retention audit", "how long do we keep transcripts", "we still have data from 2018", conflicting retention obligations, or preparing for a data protection review.

中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact.