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Earlier sources: Security
Digital security protects systems, software, accounts, and information from misuse. Explore cybersecurity, vulnerabilities, threat intelligence, cryptography, privacy, and identity, with links to the underlying advisories and research.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗650 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Silence of Commit Messages: An Empirical Study for Vulnerability Commit Message Generation using Large Language Models ↗
The vulnerability commit message serves as crucial metadata for maintaining software within version control systems. Nonetheless, manually crafted vulnerability commit messages often lack detail or exhibit inconsistent formatting. Recently, the growing use of Large Language Models (LLMs) for code and natural language comprehension has opened avenues to automate the crafting of these messages. This paper systematically and thoroughly explores the generation of security patch commit messages in the context of LLMs, delving into topics such as dataset construction, evaluation method design, and t…
- OpenAlex · Published · First archived
Fine-Grained Privacy Leakage Detection in OpenHarmony Apps ↗
In recent years, the distributed operating system OpenHarmony has gained significant popularity. As the number of OpenHarmony apps grows rapidly, privacy abuse and data leakage have emerged as critical concerns. However, the untyped and highly flexible nature of Ark bytecode poses substantial challenges. We propose HScope, a novel fine-grained program analysis framework designed to directly analyze OpenHarmony app bytecode and identify privacy risks. HScope employs abstract interpretation to model the dynamic behaviors of OpenHarmony apps, enabling precise resolution of indirect calls and the…
- OpenAlex · Published · First archived
How Safe Is Your Screen? Understanding and Detecting Privacy Leaks in Sensitive Activities ↗
Android apps handle sensitive data, often displayed on screens (i.e., Activities), and protecting these activities is vital for ensuring user privacy. Several studies have demonstrated the risk of private data leakage via screen capture and identified malware exploiting this vulnerability. To mitigate such threats, Google introduced FLAG_SECURE, an activity-level security feature that protects an Activity when set by blocking screen capture and restricting display on non-secure devices. Proper usage of this security feature could significantly reduce data leakage risks. However, to the best of…
- OpenAlex · Published · First archived
A Semantically Oriented Method for Knowledge Representation in Artificial Intelligence Systems for Cybersecurity ↗
This paper proposes a semantically oriented knowledge-representation method for transforming primary cyber-event data into structured semantic knowledge to support explainable reasoning in cybersecurity decision-making. The core contribution is a transformation mechanism from primary semantic information (PSI) to secondary semantic information (SSI), based on a frame model of network events and attack patterns and followed by rule-based logical inference. This inference process maps semantic predicates to MITRE Adversarial Tactics, Techniques, and Common Knowledge (MITRE ATT&CK) techniques and…
- OpenAlex · Published · First archived
When Optimizations Backfire: The Paradox of Plaintext Optimizations in Privacy-Preserving ML Compilers ↗
Growing concerns about data security and privacy have fueled the widespread adoption of Privacy-Preserving Machine Learning (PPML). Cryptography-based PPML, which allows computation directly on encrypted data, significantly mitigates data leakage risks. To facilitate its adoption, Ciphertext Machine Learning Compilers (CMLCs) automate the translation of high-level ML procedures into low-level circuits for encrypted data. Recently, CMLCs have increasingly adopted infrastructure from Plaintext Machine Learning Compilers (PMLCs). While integrating Plaintext-Domain Optimization Passes (PDOPs) into…
- OpenAlex · Published · First archived
PatchPorter: LLM-Driven Security Patch Porting via Version Tracing and Context Selection for NPM ↗
Third-Party Libraries are widely used in modern software development, yet their vulnerabilities pose serious security risks. This issue is particularly severe in the NPM ecosystem, where high-risk 1-day vulnerabilities can remain unpatched for extended periods. Although upgrading to the latest patched version is commonly recommended, it often causes major compatibility issues. Patch porting offers an effective solution to this challenge. However, existing patch porting methods are mainly designed for C and have two limitations when applied to NPM. First, they can be brittle in precisely locali…
- OpenAlex · Published · First archived
Sifting the Noise: A Comparative Study of LLM Agents in Vulnerability False Positive Filtering ↗
Static Application Security Testing (SAST) tools are essential for identifying software vulnerabilities, but they often produce a high volume of False Positives (FPs), imposing a substantial manual triage burden on developers. Recent advances in Large Language Model (LLM) agents offer a promising direction by enabling iterative reasoning, tool use, and environment interaction to refine SAST alerts. However, the comparative effectiveness of different LLM-based agent architectures for FP filtering remains poorly understood. In this paper, we present a comparative study of three state-of-the-art…
- OpenAlex · Published · First archived
SymWeb: Feedback-Driven Context Exploration and Context-Aware Symbolic Execution for Browser-Embedded WebAssembly Vulnerability Detection ↗
Browser-deployed WebAssembly (Wasm) modules often inherit memory-safety bugs from C and C++-style code, yet exploiting, and even reaching, these bugs in the Web threat model is fundamentally context-dependent. JavaScript (JS) controls the exported-call schedule and constructs the Wasm entry state, including arguments, globals, and linear-memory layouts, from attacker-influenced web inputs. This makes both Wasm-only analysis, which assumes static initial states, and prior browser-based testing such as Wemby ineffective. Wemby generates a fixed, Wasm-agnostic context pool and then only mutates W…
- CISA · Added to KEV · First archived
CVE-2026-104286: Fortinet FortiMail Path Traversal Vulnerability ↗
Fortinet FortiMail contains a path traversal and an improper neutralization of NULL byte or NULL character vulnerability that may allow an unauthenticated attacker to write arbitrary files on the underlying system via crafted HTTP or HTTPS requests. Required action: Apply mitigations in accordance with vendor instructions, ensuring compliance with CISA’s BOD 26-04 Prioritizing Security Updates Based on Risk (see URL in Notes) guidance and CISA’s “Forensics Triage Requirements” (see URL in Notes). Follow applicable BOD 26-04 guidance for cloud services or discontinue use of the product if mitig
- Hacker News · Posted on Hacker News · First archived
Vulnerability disclosures double to 10k per month as AI fuels exploitation ↗
Hacker News discussion.
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Security
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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