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🗓️ 11 October 2018
⏱️ 6 minutes
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| 0:00.0 | Hello, welcome to the Thursday, October 11th, 2018 edition of the Science and the Storm Center's |
| 0:06.6 | Stormcast. My name is Johannes Ulrich, and I'm recording from Honolulu, Hawaii. |
| 0:14.0 | WhatsApp fixed a critical vulnerability that was originally discovered by Natalie Silvanovich with Google's Project Zero. The vulnerability |
| 0:23.9 | was triggered by a malformed RTP packet and with trigger a heap memory corruption so code execution |
| 0:32.2 | would certainly be possible. However, the proof of concept exploit released would just crash the application. |
| 0:40.4 | To be affected by this vulnerability, a victim would have to accept a malicious call via |
| 0:46.8 | WhatsApp and then the ad hacker would use a patch similar to the one provided with the |
| 0:52.4 | proof of concept in order to inject these |
| 0:55.4 | malformed RTP packets. So remote code execution may be possible however the |
| 1:01.4 | current proof of concept exploit only triggers the denial of service. And |
| 1:07.8 | Salesforce released another neat library to fingerprint encrypted connections. |
| 1:13.6 | It's the hash library, I guess, is how you pronounce it, H-A-S-S-S-H, and as the name sort of implies, it fingerprints SSH. |
| 1:23.6 | The idea is similar to Salesforce's JA3 library that they already open sourced a while ago. |
| 1:31.3 | JA3 does profile SSL connections by looking at various artifacts in the SL or TLS handshake. |
| 1:40.3 | Now with the hash library, they essentially apply the same technique to the SSH handshake. |
| 1:47.0 | SSH has a number of different options, different crypto algorithms are supported and the like. |
| 1:53.0 | So essentially what it does is, it looks at the handshake, calculates a fingerprint of the request coming in from the client and then gives you this |
| 2:03.3 | fingerprint that should identify specific client software. |
| 2:07.6 | Now in my experience with JA3, the simplest way to use it is to use it as a plugin for |
| 2:13.5 | tool like pro and then you get a summary of all these fingerprints. |
| 2:18.0 | You can look for anomalies there. |
| 2:20.4 | You could also look for mismatches between the client identifier sent by a client |
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