697 matches found
CISA and Partners Release Update to Malware Analysis Report BRICKSTORM Backdoor
Today, the Cybersecurity and Infrastructure Security Agency CISA, National Security Agency, and Canadian Centre for Cyber Security released an update to the Malware Analysis Report BRICKSTORM Backdoor with indicators of compromise IOCs and detection signatures for additional BRICKSTORM samples...
📄 Samsung QuramDng Out-Of-Bounds Write
Samsung QuramDng has an invalid LossyJpeg component assumption that leads to an out-of-bounds write. BACKGROUND Samsung Android uses an internal DNG decoding library, QuramDng in libimagecodec.quram.so, to decode images in com.samsung.ipservice and com.samsung.gallery3d. Samsung Gallery will deco...
CLSA-2025-1764688338 gstreamer1-plugins-good: Fix of CVE-2024-47537
CVE-2024-47537: qtdemux: fix integer overflow when allocating the samples table for fragmented MP4...
Clustering Malware at Scale: A First Full-Benchmark Study
Recent years have shown that malware attacks still happen with high frequency. Malware experts seek to categorize and classify incoming samples to confirm their trustworthiness or prove their maliciousness. One of the ways in which groups of malware samples can be identified is through malware...
JLSEC-2025-304 A vulnerability was found in the libtiff library
A vulnerability was found in the libtiff library. This security flaw causes a heap buffer overflow in extractContigSamples32bits, tiffcrop.c...
JLSEC-2025-284 LibTIFF 4.4.0 has an out-of-bounds write in extractContigSamplesShifted24bits in...
LibTIFF 4.4.0 has an out-of-bounds write in extractContigSamplesShifted24bits in tools/tiffcrop.c:3604, allowing attackers to cause a denial-of-service via a crafted tiff file. For users that compile libtiff from sources, the fix is available with commit cfbb883b...
How Can We Effectively Use LLMs for Phishing Detection?: Evaluating the Effectiveness of Large Language Model-Based Phishing Detection Models
Large language models LLMs have emerged as a promising phishing detection mechanism, addressing the limitations of traditional deep learning-based detectors, including poor generalization to previously unseen websites and a lack of interpretability. However, LLMs' effectiveness for phishing...
Astra Linux – Vulnerability found in Linux 6.1, Linux 6.12
In the Linux kernel, the following vulnerability has been resolved: comedi: Make insnrwemulatebits handle insn-n samples. The insnrwemulatebits function is used as a default handler for INSNREAD instructions for sub-devices that have a handler for INSNBITS but not for INSNREAD. Similarly, it is...
Astra Linux – Vulnerability found in Linux 6.1, Linux 6.12
In the Linux kernel, the following vulnerability has been resolved: Comedi: Fixed the initialization of data for instructions that write to sub-devices. It is known that some Comedi sub-device instruction handlers access data elements beyond the first insn-n elements in some cases. The doinsnioct...
Astra Linux – Vulnerability found in Linux 6.1, Linux 6.12
In the Linux kernel, the following vulnerability has been resolved: comedi: Fixed the use of uninitialized data in insnrwemulatebits. For Comedi INSNREAD and INSNWRITE instructions on “digital” subdevices subdevice types COMEDISUBDDI, COMEDISUBDDO, and COMEDISUBDDIO, it is common for the subdevic...
APThreatHunter: An Automated Planning-Based Threat Hunting Framework
Cyber attacks threaten economic interests, critical infrastructure, and public health and safety. To counter this, entities adopt cyber threat hunting, a proactive approach that involves formulating hypotheses and searching for attack patterns within organisational networks. Automating cyber thre...
CVE-2025-61301
Denial-of-analysis in reporting/mongodb.py and reporting/jsondump.py in CAPEv2 commit 52e4b43, on 2025-05-17 allows attackers who can submit samples to cause incomplete or missing behavioral analysis reports by generating deeply nested or oversized behavior data that trigger MongoDB BSON limits o...
Injection, Attack and Erasure: Revocable Backdoor Attacks Via Machine Unlearning
Backdoor attacks pose a persistent security risk to deep neural networks DNNs due to their stealth and durability. While recent research has explored leveraging model unlearning mechanisms to enhance backdoor concealment, existing attack strategies still leave persistent traces that may be detect...
EUVD-2015-8844
Malware in sbrugna...
EUVD-2009-3966
Malware in sbrugna...
EUVD-2007-3944
Malware in sbrugna...
EUVD-2012-2772
Malware in sbrugna...
EUVD-2012-2770
Malware in sbrugna...
Adversarial-Resilient RF Fingerprinting: A CNN-GAN Framework for Rogue Transmitter Detection
Radio Frequency Fingerprinting RFF has evolved as an effective solution for authenticating devices by leveraging the unique imperfections in hardware components involved in the signal generation process. In this work, we propose a Convolutional Neural Network CNN based framework for detecting rog...