Tag Archives: Social Engineering

Details of a Phone Scam

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2024/02/details-of-a-phone-scam.html

First-person account of someone who fell for a scam, that started as a fake Amazon service rep and ended with a fake CIA agent, and lost $50,000 cash. And this is not a naive or stupid person.

The details are fascinating. And if you think it couldn’t happen to you, think again. Given the right set of circumstances, it can.

It happened to Cory Doctorow.

EDITED TO ADD (2/23): More scams, these involving timeshares.

Fooling an AI Article Writer

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2023/07/fooling-an-ai-article-writer.html

World of Warcraft players wrote about a fictional game element, “Glorbo,” on a subreddit for the game, trying to entice an AI bot to write an article about it. It worked:

And it…worked. Zleague auto-published a post titled “World of Warcraft Players Excited For Glorbo’s Introduction.”

[…]

That is…all essentially nonsense. The article was left online for a while but has finally been taken down (here’s a mirror, it’s hilarious). All the authors listed as having bylines on the site are fake. It appears this entire thing is run with close to zero oversight.

Expect lots more of this sort of thing in the future. Also, expect the AI bots to get better at detecting this sort of thing. It’s going to be an arms race.

Massive Data Breach at Uber

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/09/massive-data-breach-at-uber.html

It’s big:

The breach appeared to have compromised many of Uber’s internal systems, and a person claiming responsibility for the hack sent images of email, cloud storage and code repositories to cybersecurity researchers and The New York Times.

“They pretty much have full access to Uber,” said Sam Curry, a security engineer at Yuga Labs who corresponded with the person who claimed to be responsible for the breach. “This is a total compromise, from what it looks like.”

It looks like a pretty basic phishing attack; someone gave the hacker their login credentials. And because Uber has lousy internal security, lots of people have access to everything. So once a hacker gains a foothold, they have access to everything.

This is the same thing that Mudge accuses Twitter of: too many employees have broad access within the company’s network.

More details. Slashdot thread.

EDITED TO ADD (9/20): More details.

Problems with Multifactor Authentication

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2021/10/problems-with-multifactor-authentication.html

Roger Grimes on why multifactor authentication isn’t a panacea:

The first time I heard of this issue was from a Midwest CEO. His organization had been hit by ransomware to the tune of $10M. Operationally, they were still recovering nearly a year later. And, embarrassingly, it was his most trusted VP who let the attackers in. It turns out that the VP had approved over 10 different push-based messages for logins that he was not involved in. When the VP was asked why he approved logins for logins he was not actually doing, his response was, “They (IT) told me that I needed to click on Approve when the message appeared!”

And there you have it in a nutshell. The VP did not understand the importance (“the WHY”) of why it was so important to ONLY approve logins that they were participating in. Perhaps they were told this. But there is a good chance that IT, when implementinthe new push-based MFA, instructed them as to what they needed to do to successfully log in, but failed to mention what they needed to do when they were not logging in if the same message arrived. Most likely, IT assumed that anyone would naturally understand that it also meant not approving unexpected, unexplained logins. Did the end user get trained as to what to do when an unexpected login arrived? Were they told to click on “Deny” and to contact IT Help Desk to report the active intrusion?

Or was the person told the correct instructions for both approving and denying and it just did not take? We all have busy lives. We all have too much to do. Perhaps the importance of the last part of the instructions just did not sink in. We can think we hear and not really hear. We can hear and still not care.

Using AI to Scale Spear Phishing

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2021/08/using-ai-to-scale-spear-phishing.html

The problem with spear phishing is that it takes time and creativity to create individualized enticing phishing emails. Researchers are using GPT-3 to attempt to solve that problem:

The researchers used OpenAI’s GPT-3 platform in conjunction with other AI-as-a-service products focused on personality analysis to generate phishing emails tailored to their colleagues’ backgrounds and traits. Machine learning focused on personality analysis aims to be predict a person’s proclivities and mentality based on behavioral inputs. By running the outputs through multiple services, the researchers were able to develop a pipeline that groomed and refined the emails before sending them out. They say that the results sounded “weirdly human” and that the platforms automatically supplied surprising specifics, like mentioning a Singaporean law when instructed to generate content for people living in Singapore.

While they were impressed by the quality of the synthetic messages and how many clicks they garnered from colleagues versus the human-composed ones, the researchers note that the experiment was just a first step. The sample size was relatively small and the target pool was fairly homogenous in terms of employment and geographic region. Plus, both the human-generated messages and those generated by the AI-as-a-service pipeline were created by office insiders rather than outside attackers trying to strike the right tone from afar.

It’s just a matter of time before this is really effective. Combine it with voice and video synthesis, and you have some pretty scary scenarios. The real risk isn’t that AI-generated phishing emails are as good as human-generated ones, it’s that they can be generated at much greater scale.

Defcon presentation and slides. Another news article

Hiding Malware in Social Media Buttons

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2020/12/hiding-malware-in-social-media-buttons.html

Clever tactic:

This new malware was discovered by researchers at Dutch cyber-security company Sansec that focuses on defending e-commerce websites from digital skimming (also known as Magecart) attacks.

The payment skimmer malware pulls its sleight of hand trick with the help of a double payload structure where the source code of the skimmer script that steals customers’ credit cards will be concealed in a social sharing icon loaded as an HTML ‘svg’ element with a ‘path’ element as a container.

The syntax for hiding the skimmer’s source code as a social media button perfectly mimics an ‘svg’ element named using social media platform names (e.g., facebook_full, twitter_full, instagram_full, youtube_full, pinterest_full, and google_full).

A separate decoder deployed separately somewhere on the e-commerce site’s server is used to extract and execute the code of the hidden credit card stealer.

This tactic increases the chances of avoiding detection even if one of the two malware components is found since the malware loader is not necessarily stored within the same location as the skimmer payload and their true purpose might evade superficial analysis.

Trape – OSINT Analysis Tool For People Tracking

Post Syndicated from original https://www.darknet.org.uk/2020/11/trape-osint-analysis-tool-for-people-tracking/?utm_source=rss&utm_medium=social&utm_campaign=darknetfeed

Trape – OSINT Analysis Tool For People Tracking

Trape is an OSINT analysis tool, which allows people to track and execute intelligent social engineering attacks in real-time. It was created with the aim of teaching the world how large Internet companies could obtain confidential information.

Example types of information are the status of sessions of their websites or services and control their users through their browser, without their knowledge. It has evolved with the aim of helping government organizations, companies and researchers to track the cybercriminals.

Read the rest of Trape – OSINT Analysis Tool For People Tracking now! Only available at Darknet.