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Evaluating Large Language Models' Capability to Launch Fully Automated
  Spear Phishing Campaigns: Validated on Human Subjects

Evaluating Large Language Models' Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects

30 November 2024
Fred Heiding
Simon Lermen
Andrew Kao
B. Schneier
A. Vishwanath
ArXivPDFHTML

Papers citing "Evaluating Large Language Models' Capability to Launch Fully Automated Spear Phishing Campaigns: Validated on Human Subjects"

5 / 5 papers shown
Title
LLMs unlock new paths to monetizing exploits
LLMs unlock new paths to monetizing exploits
Nicholas Carlini
Milad Nasr
Edoardo Debenedetti
Barry Wang
Christopher A. Choquette-Choo
Daphne Ippolito
Florian Tramèr
Matthew Jagielski
AAML
13
0
0
16 May 2025
RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents
RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents
Sid Black
Asa Cooper Stickland
Jake Pencharz
Oliver Sourbut
Michael Schmatz
Jay Bailey
Ollie Matthews
Ben Millwood
Alex Remedios
Alan Cooney
ELM
142
0
0
21 Apr 2025
Frontier AI's Impact on the Cybersecurity Landscape
Frontier AI's Impact on the Cybersecurity Landscape
Wenbo Guo
Yujin Potter
Tianneng Shi
Zhun Wang
Andy Zhang
Dawn Song
52
1
0
07 Apr 2025
Adaptively evaluating models with task elicitation
Davis Brown
Prithvi Balehannina
Helen Jin
Shreya Havaldar
Hamed Hassani
Eric Wong
ALM
ELM
91
0
0
03 Mar 2025
Merger-as-a-Stealer: Stealing Targeted PII from Aligned LLMs with Model Merging
Merger-as-a-Stealer: Stealing Targeted PII from Aligned LLMs with Model Merging
Lin Lu
Zhigang Zuo
Ziji Sheng
Pan Zhou
MoMe
50
0
0
22 Feb 2025
1