s2
--:--:--UTC

Searching APEX

Starting…

  1. Searching Threats, IOCs & Threat Intelligence locally
  2. Querying external providers
  3. Asking AI Forensic Validator
  4. Creating new entry from validated hit

0s elapsed

TF-MAL-php.ensikology

📛 Threat Title

Malware family: Ensikology

Category: Ensikology First seen: Last updated: Source: ThreatFox Malwares

Description

ThreatFox malware family `php.ensikology`. Printable name: Ensikology. Aliases: Ensiko.

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 php.ensikology VT: VT base fetch failed: HTTPError: 429 Client Error: Too Many Requests for url: https://www.virustotal.com/api/v3/domains/php.ensikology

IOC database

Type
domain
Value
php.ensikology
First seen
Last seen
Attached to this threat
Appears in
1 threat
Description
Extracted from Threat TF-MAL-php.ensikology

Open the full IOC page →

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/php.ensikology

References (1)

Remediations (10)

  • 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.

  • web:ieeexplore.ieee.org

    Due to the diversity of malware types and families and the rapid increase of malware attacks, there is a need to develop a way to find and categorize the malware to its families. Traditional malware classification techniques depend on malware signatures, which are known to be associated with certain malware families or variants. However, the rapid increase of new malware variants with unknown ...

  • web:malpedia.caad.fkie.fraunhofer.de

    Details for the Ensikology malware family including references, samples and yara signatures.

  • 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.

  • 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.

  • web:www.first.org

    Introduction Overview The Malware Analysis Framework, developed by FIRSTs Malware Analysis Special Interest Group (SIG), is a document aimed to help CSIRTs establish their own malware analysis workflow (s). It provides step-by-step guidance in all workflow phases on how to develop malware analysis capabilities within CSIRTs. This document also lists supporting resources that can further assist ...

  • 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 ...

  • web:www.ncsc.gov.uk

    This guidance helps private and public sector organisations deal with the effects of malware (which includes ransomware). It provides actions to help organisations prevent a malware infection, and also steps to take if you're already infected. Following this guidance will reduce: the likelihood of becoming infected the spread of malware throughout your organisation the impact of the infection

  • web:www.researchgate.net

    Prevention and detection of eBPF-based malware is also explored, with the goal of providing organizations or legitimate users of eBPF techniques to harden their systems against eBPF-based malware ...

  • web:www.sciencedirect.com

    Due to the rapid development of anti-virus engines, the family information of malware can be obtained from the anti-virus labels (abbreviated as AV labels1) generated by various vendors. A standard AV label consists of platform, malware type, malware family , variant component, and additional information that is prepended or appended to the name.

AI Forensic Analysis

Only Available for Registered Users. Sign in to view.