Detecting Aimbot Cheaters in MOGs
2026-06-09T07:23:31Z•50ba950a7d90cbb06bea22515a0e29f84eb5c1a1966d36db30d2f4bae56b997d
DRAMIDSMOLOTRowHammerSASTScaleDisturbVLM-jailbreakadversarial-MLadversarial-patchesanomaly-detectionanti-cheatensemble-modelsflowchart-attackshoneytokensintrusion-detectionisolation-forestmajority-votemalicious-package-detectionmedian-smoothingmultilingual-securityread-disturbancestatic-analysissupply-chain-securityvision-language-modelsvisual-aimbot
What happened
This collection of papers from arXiv (cs.CR) presents new offensive and defensive research across hardware, machine learning, cryptography, and software-supply-chain security. Key contributions: PATCH — adversarial patch honeytokens to detect or disrupt visual aimbots in multiplayer games (90%+ white-box detection; 60–90% cross-model transferability); MLingualFC — a multilingual flowchart-based benchmark exposing jailbreak vulnerabilities in VLMs across multiple scripts and languages; IDS-Anta++ / SHIELD-IDS — structurally heterogeneous ensembles and layered preprocessing that improve IDSrob u
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 50ba950a7d90cbb06bea22515a0e29f84eb5c1a1966d36db30d2f4bae56b997d
- Enrichment time
- 2026-06-09T07:23:31Z
- AI-assisted enrichment
- Yes
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