As can seen from the BGP output, we were using a /32 route going over AS 34109. This was highly suspicious for two reasons. First, a /32 route refers only to a single IP address. Except in special cases, routes are normally /24 (256 hosts) or larger. Second, the AS 34109 belongs to CB3ROB which is an Internet provider that has actually been in conflict with Spamhaus (see: spamhaus; allspammedup; theregister). Certainly they weren’t running a legitimate Spamhaus server. It seems clear that the CB3ROB network hijacked one (or more) of the IP addresses of Spamhaus, and installed a DNS server there which incorrectly returns positive results to every query. The result causes harm to Spamhaus users and their customers, making Spamhaus unusable for anyone unable to correct the problem as we did, and perhaps even undermining the credibility of Spamhaus itself.

"It is a cyber attack ... pursued by an entity that has the characteristics of a state actor," [Romanian secret service] SRI spokesman Sorin Sava told Reuters [...]. "Our estimations show the attack is certainly relevant to Romania's national security taking into account the profile of the compromised entities." [...]

In this case, computer experts say an attacker from the former Soviet Union could be more likely. "MiniDuke" in some ways resembles a banking fraud Trojan dubbed "TinBa" believed to have been created by Russian criminal hackers.

Cyber criminals have targeted government officials in more than 20 countries, including Ireland and Romania, in a complex online assault seen rarely since the turn of the millennium. The attack, dubbed "MiniDuke" by researchers, has infected government computers as recently as this week in an attempt to steal geopolitical intelligence, according to security experts.

'So far we have performed more than 1000 transactions at more than 20 ATMs and a number of POS terminals, and are collating a data set for statistical analysis. We have developed a passive transaction logger which can be integrated into the substrate of a real bank card, which records up to 100 unpredictable numbers in its EEPROM. Our analysis is ongoing but so far we have established non-uniformity of unpredictable numbers in half of the ATMs we have looked at.

First, there is an easier attack than predicting the RNG. Since the unpredictable number is generated by the terminal but the relying party is the issuing bank, any intermediate party – from POS terminal software, to payment switches, or a middleman on the phone line – can intercept and superimpose their own choice of UN. Attacks such as those of Nohl and Roth, and MWR Labs show that POS terminals can be remotely hacked simply by inserting a sabotaged smartcard into the terminal.

We investigate a family of poisoning attacks against Support Vector Machines (SVM). Such attacks inject specially crafted training data that increases the SVM's test error. Central to the motivation for these attacks is the fact that most learning algorithms assume that their training data comes from a natural or well-behaved distribution. However, this assumption does not generally hold in security-sensitive settings. As we demonstrate, an intelligent adversary can, to some extent, predict the change of the SVM's decision function due to malicious input and use this ability to construct malicious data. The proposed attack uses a gradient ascent strategy in which the gradient is computed based on properties of the SVM's optimal solution. This method can be kernelized and enables the attack to be constructed in the input space even for non-linear kernels. We experimentally demonstrate that our gradient ascent procedure reliably identifies good local maxima of the non-convex validation error surface, which significantly increases the classifier's test error.