TF-MAL-js.bateleur
📛 Threat Title
Malware family: Bateleur
Description
ThreatFox malware family `js.bateleur`. Printable name: Bateleur.
Indicators of Compromise (1)
Each indicator is enriched from the IOC database, threat-intel feed corroboration (Threat Hunt) and VirusTotal. Click one to expand.
domain
js.bateleur
VT: VT base fetch failed: HTTPError: 429 Client Error: Too Many Requests for url: https://www.virustotal.com/api/v3/domains/js.bateleur
IOC database
- Type
- domain
- Value
js.bateleur- First seen
- Last seen
- Attached to this threat
- Appears in
- 1 threat
- Description
- Extracted from Threat TF-MAL-js.bateleur
Threat Hunt — feed corroboration
Not present in any configured threat-intel feed.
Details From VirusTotal
VirusTotal: VT base fetch failed: HTTPError: 429 Client Error: Too Many Requests for url: https://www.virustotal.com/api/v3/domains/js.bateleur
References (1)
- ThreatFox: IOCs for this family ThreatFox Malwares
Remediations (10)
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web:arxiv.org
Interpretable models are especially important in ad-versarial domains such as malware analysis, where understanding the rationale behind a classification can guide remediation efforts and enhance model robust-ness. This paper proposes a novel approach for detect-ing and explaining concept drift in malware families over time.
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web:dl.acm.org
In response, Artificial Intelligence (AI) models are increasingly leveraged to enhance malware classification and remediation efforts. However, while such models trained to classify malware datasets often perform well in controlled environments, research increasingly shows that conventional AI-based malware classifiers struggle to generalize to ...
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web:malpedia.caad.fkie.fraunhofer.de
This page gives an overview of all malware families that are covered on Malpedia, supplemented with some basic information for each family .
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web:marcusbotacin.github.io
Malware classification is a critical task in computer security since it allows the identification and mitigation of potential cybersecurity threats. Convolutional Neural Networks (CNN) have proven to be an efective tool in malware detection, especially when combined with the transfer learning technique.
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web:windowsforum.com
The emergence of RESURGE signals more than just another entry in a long line of malware threats. According to CISA, RESURGE contains advanced persistence features inherited from the SPAWNCHIMERA malware family—a group notorious for its ability to survive system reboots and avoid simplistic remediation .
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web:www.breachsense.com
Complete malware remediation now requires addressing both the infected endpoint and the stolen authentication data. Your malware incident response playbook must account for both.
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web:www.cisa.gov
It highlights technical approaches to uncovering malicious activity and includes mitigation steps according to best practices. The purpose of this report is to enhance incident response among partners and network administrators along with serving as a playbook for incident investigation.
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web:www.microsoft.com
Kazuar, a sophisticated malware family attributed to the Russian state actor Secret Blizzard, has been under constant development for years and continues to evolve in support of espionage-focused operations. Over time, Kazuar has expanded from a relatively traditional backdoor into a highly modular peer-to-peer (P2P) botnet ecosystem designed to enable persistent, covert access to target ...
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web:www.nature.com
This study proposes a hierarchical deep learning framework for Portable Executable (PE) malware detection and family categorization, underpinned by a novel Doubly Regularized Binary Cross-Entropy ...
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web:www.ncsc.gov.uk
How to defend organisations against malware or ransomware attacks.
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