Search: “http-parsing”

Trends in Web Threats: Old Web Skimmer Still Active Today

Unit 42 detected 577,000 landing URL incidents in Q1 2022, with an old web skimmer family still actively stealing payment card data.

Palo Alto Unit 42 detected 577,275 landing URL incidents (116,643 unique) and 2,043,862 malicious host URL incidents (180,370 unique) between January and March 2022. Web threat volumes declined after the November 2021 holiday peak, but an old web skimmer family remained active. Business and economy sites overtook personal sites as the most common apparently benign entry points. Most malicious domains geolocated to the United States, Germany, and Russia, though proxy servers and VPNs obscure true locations.

Palo Alto Unit 42·Aug 17, 13:05 UTC · Aug 17, 2026Research

Advanced URL Filtering Archives

Palo Alto Networks markets Advanced URL Filtering as combining a malicious URL database with real-time ML and DL web protection.

The Unit 42 blog page is a product category archive for Advanced URL Filtering. The product description states it combines a malicious URL database with a real-time web protection engine powered by machine learning and deep learning models. No research findings, incidents, or vulnerabilities are discussed.

Palo Alto Unit 42·Sep 8, 14:27 UTC · 8d agoIndustry 6 sources

PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents

PARSER uses parallel reader subagents and an RL-trained lead agent for long-context QA, beating baselines and cutting latency up to 11x.

The PARSER paper decouples reading from reasoning: frozen subagents each read one document chunk in parallel while an RL-optimized lead agent iteratively broadcasts queries and aggregates evidence in scatter-gather rounds. On multi-hop QA with 7K to 896K token contexts, a 4B-backbone PARSER beats the strongest sequential memory baseline by 5.7 points on average and 12.0 points at 896K tokens, and a 9B version surpasses DeepSeek-V4-Pro by 6.3 points. Controlled experiments show robustness to evidence position, order, and distance perturbations, with inference latency reduced by up to 11x.

Hugging Face daily papers·Sep 5, 20:00 UTC · 10d agoAI research1

Trends in Web Threats in CY Q2 2022: Malicious JavaScript Downloaders Are Evolving

Unit 42 detected 751,000 landing URL incidents in Q2 2022 and documented malicious JavaScript downloaders evolving to evade detection.

Unit 42 detected 751,331 landing URL incidents (253,644 unique) and 1,744,629 malicious host URL incidents (256,844 unique) from April through June 2022. Total landing URL incidents rose compared with Q1 2022, and unique host URL incidents grew 42%, indicating attackers deploying more variants. The report includes a case study of a JavaScript downloader campaign demonstrating new evasion techniques. Personal sites, blogs, and business sites were the top apparently benign entry points.

Palo Alto Unit 42·Aug 17, 13:05 UTC · Aug 17, 2026Research

PEEP Turns Chrome and Edge Into Post-Compromise Backdoors for Host Command Execution

SOCRadar disclosed PEEP, a post-exploitation Chromium extension toolkit that turns Chrome and Edge into host-level backdoors via native messaging and C2 polling.

SOCRadar researchers detailed PEEP, a Chromium-based post-exploitation toolkit masquerading as a 'Smart Bookmarks' extension injected directly into Chrome and Edge profiles by forging Secure Preferences integrity values, bypassing Web Store checks. A native-messaging host binary (nm_host.exe) extends the browser agent to host-level command execution, file management, credential theft, and session hijacking, while the extension polls C2 endpoints at 206.237.30.232 or xfjcc.fun every 30 seconds over plaintext HTTP and exfiltrates browsing history, cookies, and tab metadata. PEEP is derived from the open-source RedExt red teaming framework, adds PowerShell persistence scripts, and includes a Linux-targeting Python script, suggesting cross-platform intent. The activity is unattributed but contains Chinese-language artifacts; a C2 /health endpoint showed 34 agent entries and 10 active sessions.

The Hacker News·Sep 7, 18:12 UTC · 8d agoMalware in the wild

Understanding the Privacy-Preserving Potential of HTTP/2 Against Webpage Fingerprinting

Researchers show HTTP/2 features can emulate website fingerprinting defenses like FRONT and Tamaraw with tunable privacy-overhead trade-offs.

An arXiv paper demonstrates that application-layer defenses such as HTTPOS, LLaMA, FRONT, ALPaCA, and Tamaraw can be emulated through HTTP/2 features at both the client and server side, including proactive resource suggestion, multiplexing, and flow control. The authors propose a unified evaluation blueprint that calibrates defense parameters per dataset, combines practical attacks with information-theoretic leakage estimators, and measures overheads to map each defense's privacy-overhead trade-offs.

arXiv cs.CR·Sep 4, 13:16 UTC · 12d agoResearch

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:39 UTC · 5d agoAI research1

Atlas: Efficient Verifiable Semantic Search

Atlas delivers zero-knowledge proofs for HNSW semantic search, verifying RAG retrieval in under a second on SIFT1M and 2.0 seconds at 100M vectors.

Atlas lets a search provider prove that a query was answered correctly against a committed HNSW index without revealing the index, addressing provider deviations like truncation or bias. It combines offline preprocessing, a fixed-size-state restructuring of HNSW with a correctness proof, and timestep-tagged batching of per-step arguments. The system proves queries in under a second on SIFT1M and 2.0 seconds at 100 million vectors while preserving plaintext HNSW recall, and proven retrieval maintains end-to-end RAG answer quality at lower cost than prior verifiable retrieval systems.

arXiv cs.CR·Sep 10, 17:30 UTC · 5d agoResearch1

'HTTP Terminator' Hunts for Novel Desync Attacks

PortSwigger's James Kettle discusses HTTP Terminator, an AI-powered open source tool that uncovered new HTTP request-smuggling (desync) techniques.

PortSwigger researcher James Kettle spoke with Dark Reading about HTTP Terminator, an AI-powered open source tool built to hunt for novel HTTP desync vulnerabilities. The tool has already discovered new HTTP request-smuggling techniques, extending Kettle's prior desync research.

Dark Reading·Aug 26, 19:54 UTC · 20d agoTools

Unifying Conformal Language Tasks with In-Context Ensembles

Researchers propose Conformal Relevance, which builds conformal score functions via in-context example curation and ensembling to improve conciseness across seven NLP tasks.

The paper targets NLP tasks like summarization and extractive QA that reduce to retrieving content under coverage and conciseness constraints. Conformal Relevance replaces hand-engineered LLM scoring prompts with curated in-context examples and ensembles, maintaining coverage guarantees while improving conciseness with minimal manual input. The authors demonstrate the framework on seven NLP tasks and contribute theory, including a complementarity condition for when ensembling improves worst-case sentence scores and a saturation bound on ensemble gains.

Hugging Face daily papers·Sep 1, 20:00 UTC · 14d agoAI research1

terms.txt: A Consent and Compensation Protocol for Agentic Web Access

terms.txt specifies a robots.txt-style protocol for per-path, per-purpose AI crawler consent and compensation, with enforcement adding 0.20-0.65 ms per request.

The paper documents that automated clients now make up most web requests, that training dominates Cloudflare-classified crawling, and that the largest AI platforms fetch thousands of pages per returned visitor while robots.txt cannot express identity, purpose, terms, or price. It specifies terms.txt plus an origin-enforced exchange using Web Bot Auth signatures, signed intent, delegation tokens, HTTP 402 negotiation, and signed receipts. A dependency-free implementation adds 0.20 to 0.65 ms per request on one vCPU.

arXiv cs.CR·Sep 10, 07:01 UTC · 6d agoResearch

CiteShade: Citation Laundering in Multi-Source Retrieval-Augmented Generation and Its Counterfactual Defense

CiteShade attack makes RAG models cite trusted sources for attacker-chosen wrong answers, raising wrong-answer rate from 0.01 to 0.68.

CiteShade is presented as the first citation laundering attack against multi-source retrieval-augmented generation: an attacker controlling a single source induces a wrong answer falsely attributed to a trusted source, even while correct evidence remains in context. The attack is formalized via three necessary conditions (retrieval, generation, citation) constructible without any instructions, raising wrong-answer rate from 0.01 to 0.68 on multi-hop QA, with source deletion confirming the malicious source as causal driver. Vulnerability tracks a model's citation propensity rather than scale, reaching CLR 0.84 with explicit instruction and 0.64 without on the most citation-prone model. Perplexity filtering and citation-support checking prove insufficient; the authors propose a counterfactual defense verifying which source actually drove the answer.

arXiv cs.CR·Sep 14, 14:41 UTC · 1d agoAI safety & security1

You Get What You Sample: Evaluating Sampling Strategies for Web Security Measurements

Evaluation of 500k Tranco and 24.8M Common Crawl hosts shows Top-N domain sampling biases web security measurements; probability sampling yields unbiased estimates.

The study is the first comprehensive investigation of how sampling strategies affect web security measurement conclusions, comparing datasets and strategies across 500k Tranco domains and 24.8M Common Crawl hosts. It shows Top-N selection does not reflect the overall web distribution and may bias observed vulnerability rates, while probability-based strategies yield stable, unbiased prevalence and impact estimates. Hybrid sampling offers no advantage because its deterministic prefix consistently hurts accuracy, and the authors propose an adaptive probability-based strategy effective even when target prevalence is unknown.

arXiv cs.CR·Sep 10, 08:21 UTC · 6d agoResearch1

AI-Assisted HTTP Terminator Finds Novel HTTP Desync Techniques and Apache Zero

The Hacker News·Aug 7, 11:25 UTC · Aug 7, 2026Exploit / PoCCVE-2026-63078

Think Before You Link: Rarity, Reasoning, and Retrieval in Multilingual Entity Linking

Training-free reasoning-plus-retrieval framework lifts multilingual multimodal entity linking accuracy by 6.9% overall and up to 23.3% on rare entities.

The paper broadens rarity measurement in multimodal entity linking using knowledge-graph structural metrics beyond popularity-based pageview metrics, identifying many rare entities that popularity metrics miss. Across these rare-entity slices, state-of-the-art accuracy drops by 15.4-39.9%, exposing distinct failure modes under different rarity definitions. The proposed training-free framework iteratively searches and reasons over Wikipedia with a reasoning-capable vision-language model; experiments show reasoning and retrieval are complementary. On the MERLIN benchmark covering Hindi, Indonesian, Japanese, Tamil, and Vietnamese, the system improves overall accuracy by 6.9% and up to 23.3% on rare entities, with MERLIN-Rare test slices released.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog·Aug 26, 00:00 UTC · 21d agoAI tools & infra1

PEEP: A Browser RAT Posing as a Chrome Extension

SOCRadar's STRU analyzed PEEP, an emerging Chromium-based RAT disguised as a Chrome extension enabling post-exploitation control of browsers.

SOCRadar's Threat Research Unit (STRU) identified and analyzed PEEP, a Chromium-based post-exploitation toolkit distributed as a browser extension. PEEP provides RAT-style capabilities while posing as a legitimate Chrome extension. It is assessed as an emerging threat worth monitoring by defenders.

SOCRadar·Sep 4, 09:50 UTC · 12d agoMalware

Trends in Web Threats: Attackers Were More Active During Holiday Season

Unit 42 tracked 533,000 malicious landing URL incidents from October-December 2021, showing web threats peaked during the holiday shopping season.

Unit 42 detected 533,452 malicious landing URL incidents (120,753 unique) and 2,906,875 malicious host URL incidents (165,255 unique) from October through December 2021. Threat activity peaked in November, likely tied to Black Friday in the United States, United Kingdom, and Germany. Most malicious domains appeared to originate in the United States, followed by Russia and Germany. Personal sites, blogs, business sites, and shopping sites were the most common apparently benign entry points for attacks.

Palo Alto Unit 42·Aug 17, 13:06 UTC · Aug 17, 2026Research

Telegram Desktop Flaw Could Turn Old Chat Exports Into Data Theft Traps

ExPatch disclosed stored XSS in Telegram Desktop HTML export letting bot messages steal chat data when exports open in browsers.

ExPatch researchers Denis and Aleksander Rostilov found a stored XSS flaw (CVSS 8.2) where bot inline keyboard button text was written unescaped into HTML chat exports, executing attacker JavaScript in browsers. The payload can persist in chat history for months, exfiltrate messages, metadata, and local file paths, and rewrite the page, spreading via forwarded messages without bot membership. Telegram fixed it by applying SerializeString(), first stable fixed release 7.0.1 shipped July 14, 2026, but HTML exports created with vulnerable versions remain dangerous.

Security Affairs·Sep 15, 07:48 UTC · 1d agoVulnerability1· 1 read

CVE-2026-82617: Apache OpenNLP: ReDoS / stack exhaustion in RegexNameFinderFactory built-in EMAIL and URL patterns

Apache OpenNLP CVE-2026-82617: built-in EMAIL and URL regex name-finder patterns enable regular expression denial-of-service and stack exhaustion in affected releases.

CVE-2026-82617 affects Apache OpenNLP opennlp-core 3.0.0-M1 before 3.0.0-M6 and opennlp-tools 2.0.0 before 2.5.12. The DEFAULT_REGEX_NAME_FINDER.EMAIL and DEFAULT_REGEX_NAME_FINDER.URL patterns in RegexNameFinderFactory contain ambiguous nested quantifiers. Applications using these built-in finders on attacker-controlled input can be forced into regular expression denial of service or stack exhaustion. Fixes shipped in opennlp-tools 2.5.12 and 3.0.0-M6.

oss-security·Sep 11, 19:24 UTC · 4d agoVulnerability 2 sourcesCVE-2026-826171

Google’s new search redirects make links harder to check before you click

Google routes some search result links through encoded google.com/goto?url= redirects, breaking hover-to-verify link checks and raising scraping costs.

Google has started routing some search result links through opaque google.com/goto?url=... redirects using a custom Google-specific encoding, with the destination visible only via the redirect response's Location header. Google confirmed the rollout as an anti-abuse measure, most likely to make bulk extraction of destination URLs from search results more difficult and costly. Malwarebytes warns the change undermines the standard hover-before-clicking safety advice, while legitimate rank-tracking, SEO auditing, archival, and accessibility tools now face the same rate limits and costs as abusive scrapers.

Malwarebytes Labs·Sep 14, 14:17 UTC · 2d agoIndustry

I Am No One: Style-Aware Paraphrasing for Text Anonymization

Prompt-driven style-aware paraphrasing with LLMs cuts authorship attribution F1 by 60-70% while preserving content quality.

The paper proposes a style-aware, prompt-driven anonymization approach using pretrained LLMs to build compact stylistic profiles from minimal samples and rewrite text to suppress identifiable style markers while preserving meaning. It addresses stylometric re-identification risks in anonymized text, including ASR transcripts of meetings and call-center calls where leakage persists after acoustic anonymization. Across blog and review datasets, the approach reduces authorship attribution F1 by 60-70%, substantially outperforming both DP-based and non-DP baselines while maintaining readability.

arXiv cs.CR·Sep 11, 02:07 UTC · 5d agoResearch

Rare Not Random Using Token Efficiency for Secrets Scanning

Researcher proposes token efficiency (string length divided by BPE token count) as a better post-regex filter than entropy for secrets scanning, validated on CredData.

The post explores whether Byte-Pair Encoding tokenization can replace Shannon entropy as the primary filter for candidate secrets captured by regex in tools like Gitleaks. It defines 'token efficiency' as string length divided by token count under the cl100k_base tokenizer; secret-like strings such as GitHub tokens tokenize into many small tokens and score low, while natural text scores high. Evaluating labeled secrets from the CredData dataset shows a usable separation, with roughly 2.5 suggested as a minimum cutoff versus Gitleaks' 3.5 entropy threshold. The technique is positioned as a post-regex filtering step rather than a standalone detector.

Lobsters · security·Sep 12, 06:42 UTC · 4d agoResearch

Evidence-Grounded Retrieval for Investigation Hunt Lead Generation from CTI Reports

AHLERT generates environment-aware threat hunting leads from CTI reports using ATT&CK-seeded knowledge graph retrieval, roughly doubling F1 over flat-RAG baselines.

The paper introduces AHLERT, a system that converts Cyber Threat Intelligence reports into structured, investigable hunt leads via hybrid dense retrieval with multi-hop traversal over an MITRE ATT&CK-seeded knowledge graph and ontology-grounded RAG constrained to the defender's assets. It is LLM-agnostic and evaluated on public CTI reports for well-known APTs across proprietary and open-weight models. Hybrid evidence retrieval with ontology grounding raises mean F1 from 0.44 to 0.85, and AHLERT attains the highest effectiveness score (~86.95%) versus off-the-shelf LLMs.

arXiv cs.CR·Sep 8, 14:21 UTC · 8d agoResearch

Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretraining

Climate-ModernBERT domain-adapted encoders reach 76.3 average F1 across nine climate benchmarks, 2.8 points above vanilla ModernBERT-Base.

The authors continue pretraining ModernBERT-Base on three climate corpora - academic text, climate-filtered web data, and synthetic documents - and compare joint mixtures against parameter-space merging of specialized checkpoints. The best model achieves 76.3 average F1 across nine climate NLP benchmarks, a 2.8-point improvement over the vanilla baseline. Academic climate corpora provide the strongest adaptation signal, and parameter-space merging outperforms joint multi-source training while preserving complementary corpus information; all variants are released.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:41 UTC · 8d agoAI research

Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:32 UTC · 11d agoAI research1

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 15:49 UTC · 11d agoAI research

Google’s New Search Redirects Make It Harder to Check Where Links Lead Before Clicking

Malwarebytes reports Google's new encoded google.com/goto?url= redirects break hover-preview link checking, weakening a common phishing defense.

Google now routes some search results through opaque google.com/goto?url= redirects using custom encoding, so browser link previews no longer reveal the true destination, only the claimed label above the result. Malwarebytes found the final destination is visible only in the redirect response's Location header, complicating hover-based safety checks as well as scraping, archiving, and audit tools. The change arrives amid malvertising, search-result poisoning, and fake installer campaigns like the recent Node.js infostealer lure. Google says it deploys measures against evolving abuse but did not explain the change.

Cyber Security News·Sep 15, 12:21 UTC · 1d agoResearch

[webapps] Langflow 1.8.4 - Path Traversal to Remote Code Execution

A path traversal to remote code execution exploit for Langflow 1.8.4, a popular LLM application builder, was published on Exploit-DB.

Exploit-DB lists a proof-of-concept exploit chaining path traversal to remote code execution in Langflow 1.8.4, an open-source tool used to build LLM applications and agents. The chain allows an attacker to write arbitrary files outside the intended directory and achieve code execution on the host. The provided text does not include a CVE identifier or reports of exploitation in the wild, but RCE in a widely deployed AI tooling product is notable for defenders.

Exploit-DB·Aug 31, 00:00 UTC · 16d agoExploit / PoC1

Studying Without a Syllabus: Task-Agnostic Environment Preprocessing

Paper formalizes task-agnostic environment preprocessing, where agents study unfamiliar environments under a budget to build reusable artifacts for a frozen solver.

The paper formalizes task-agnostic environment preprocessing, where a studying system explores an environment under a budget and produces artifacts like indices, scripts, or procedural guidance for a frozen solver, without task examples or evaluation feedback. The authors compare unaided and archive-equipped meta-agents against fixed synthetic-practice and corpus-processing methods across six heterogeneous benchmarks. A meta-agent variant achieves the highest Avg@3 reward on five benchmarks, while fixed corpus processing remains best on the largest corpus benchmark. Studied artifacts reduce the test-time sampling needed to reach a given score, shifting computation from repeated test-time attempts to a pre-task study phase.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research