Results for “impersonation-detection”
52 skillsMore results
performing-brand-monitoring-for-impersonation
Detect brand impersonation attacks across domains, social media, mobile apps, and dark web channels to identify phishing campaigns, fake sites, and unauthorized brand usage.
24.6k · bundle
resemble-detect
Detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using the Resemble AI platform.
36.2k · bundle
detecting-mimikatz-execution-patterns
Hunt for Mimikatz execution using command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.
24.6k · bundle
detecting-model-extraction-attacks
Detect model stealing, model inversion, and membership inference performed through inference-API abuse by monitoring query patterns, applying output perturbation, and red-teaming your own model's extractability.
24.6k · bundle
huggingface-vision-trainer
Trains and fine-tunes vision models for object detection, image classification, and segmentation using Hugging Face Transformers on cloud GPUs, with automatic dataset validation and Hub persistence.
10.8k · bundle
tao-finetune-cosmos-embed
Fine-tune, evaluate, run inference, and export Cosmos-Embed1 video-text embedding models for tasks like text-to-video retrieval and semantic deduplication.
2.2k · bundle
tao-train-reid
Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.
2.2k · bundle
analyzing-typosquatting-domains-with-dnstwist
Detect typosquatting, homograph phishing, and brand impersonation domains using dnstwist to generate domain permutations and identify registered lookalike domains targeting your organization.
24.6k · bundle
chameleon-mixed-modal-early-fusion-foundation-models-arxiv-2
Chameleon: Mixed-Modal Early-Fusion Foundation Models
6
visor
Evaluates text-to-image models on spatial relationship accuracy using the VISOR metric, separating object detection from spatial correctness to reveal biases like object priority and merging.
3
detecting-deepfake-audio-in-vishing-attacks
Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features and classifying samples with machine learning models.
24.6k · bundle
mike-myers-expert
Adopts the voice and methodology of comedian Mike Myers to create memorable characters, catchphrases, and loving parodies for brand voices and creative writing.
6
mel-brooks-expert
Adopts the voice and comedic methodology of filmmaker Mel Brooks to craft parody, satire, and humor in responses.
6
embeddings
Explains dense vector embeddings, their key concepts, common use cases, and best practices for semantic search and RAG applications.
1
plan-antislop
Audit a codebase, UI, or copy for machine-generated tells across prose, visual/UI, code, and structure/IA, then produce a phased de-slop burndown. Use when the user says "feels AI-generated", "looks like AI slop", "reads like ChatGPT", "feels generic/soulless", or wants an authenticity/voice pass before launch.
8
shenmo-skill
沈墨(悬疑剧虚构)认知与表达框架(压缩蒸馏):创伤反杀叙事、时代灰雾、钢琴意象 触发:漫长的季节 等。虚构;禁止犯罪模仿
9 · bundle
fid
Measures distributional similarity between original GAN-generated images and their semantically manipulated counterparts using the Fréchet Inception Distance (FID) metric.
3
influence-functions-in-deep-learning-arxiv-2002-08484v3
Influence Functions in Deep Learning
6
nocaps-novel-object-captioning-at-scale-arxiv-1812-08658v2
Nocaps: Novel Object Captioning at Scale
6
llama-cpp
llama.cpp local GGUF inference + HF Hub model discovery.
1 · bundle
bmad-ml-omen
Standard reviewer for correctness and reproducibility. Use when the user asks to talk to Omen, requests a code review, or needs reproducibility verification.
0 · bundle
replicate-run
Run any Replicate model (image gen, audio, video) by version ID
118 · bundle
detecting-credential-dumping-techniques
Detect LSASS credential dumping, SAM database extraction, and NTDS.dit theft using Sysmon Event ID 10, Windows Security logs, and SIEM correlation rules.
24.6k · bundle
detecting-data-and-model-poisoning
Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.
24.6k · bundle
detecting-arp-poisoning-in-network-traffic
Detect and prevent ARP spoofing attacks using ARPWatch, Dynamic ARP Inspection, Wireshark analysis, and custom Python monitoring scripts to protect against man-in-the-middle interception.
24.6k · bundle
humanize-chinese
Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC sc
1k · bundle
detecting-anomalous-authentication-patterns
Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs.
24.6k · bundle
mantis-interleaved-multi-image-instruction-tuning-arxiv-2405
Mantis: Interleaved Multi-Image Instruction Tuning
6
verification-patterns
Provides grep-based patterns to verify that code artifacts are real implementations rather than stubs or placeholders, covering React components, API routes, database schemas, and hooks.
1
banksy-expert
Adopts the voice and methodology of the street artist Banksy to craft subversive, visual, and economically precise messaging for maximum impact.
6
tpr-fpr
Evaluates speaker verification models by computing true positive rate at fixed false positive rate thresholds, probing embedding space separation of same-speaker versus different-speaker pairs.
3
confidence-calibration-check
Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.
0
dbs-benchmark
Helps find and analyze competitors to imitate using a five-filter method, focusing on profitability and feasibility while eliminating personal bias.
check-citations
Verify academic citations against CrossRef, Semantic Scholar, and OpenAlex. Detects AI-hallucinated references, chimeric citations, and suspicious patterns.
1k · bundle
copy-paste-augmentation-for-instance-segmentation-arxiv-2012
Copy-Paste Augmentation for Instance Segmentation
6