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Data and derived information about target victims has always been key for successful attacks, both during historical wars and modern cyber wars. Ours turns out to be an era in which modern cars generate a plethora of data about their drivers, and such data could be extremely attractive for offenders. This paper seeks to assess how well modern cars protect their drivers' data. It pursues its goal at a requirement level by analysing the gaps of the privacy policies of chief automakers such as BMW and Mercedes with respect to the General Data Protection Regulation (GDPR). It is found that both brands are still imprecise about how they comply with a number of GDPR articles, hence compliance often results non-verifiable. Most importantly, while BMW exhibits slightly broader compliance, both brands still fail to comply with a number of relevant articles of the regulation. An interpretation of these findings is a non-negligible likelihood that your car may turn against you should cyberwarfare break out.

Despite their apparent simplicity, devices like smart light bulbs and electrical plugs are often perceived as exempt from rigorous security measures. However, this paper challenges this misconception, uncovering how vulnerabilities in these seemingly innocuous devices can expose users to significant risks. This paper extends the findings outlined in previous work, introducing a novel attack scenario. This new attack allows malicious actors to obtain sensitive credentials, including the victim's Tapo account email and password, as well as the SSID and password of her local network. Furthermore, we demonstrate how these findings can be replicated, either partially or fully, across other smart devices within the same IoT ecosystem, specifically those manufactured by Tp-Link. Our investigation focused on the Tp-Link Tapo range, encompassing smart bulbs (Tapo L530E, Tapo L510E V2, and Tapo L630), a smart plug (Tapo P100), and a smart camera (Tapo C200). Utilizing similar communication protocols, or slight variants thereof, we found that the Tapo L530E, Tapo L510E V2, and Tapo L630 are susceptible to complete exploitation of all attack scenarios, including the newly identified one. Conversely, the Tapo P100 and Tapo C200 exhibit vulnerabilities to only a subset of attack scenarios. In conclusion, by highlighting these vulnerabilities and their potential impact, we aim to raise awareness and encourage proactive steps towards mitigating security risks in smart device deployment.

The IoT is getting more and more pervasive. Even the simplest devices, such as a light bulb or an electrical plug, are made "smart" and controllable by our smartphone. This paper describes the findings obtained by applying the PETIoT kill chain to conduct a Vulnerability Assessment and Penetration Testing session on a smart bulb, the Tapo L530E by Tp-Link, currently best seller on Amazon Italy. We found that four vulnerabilities affect the bulb, two of High severity and two of Medium severity according to the CVSS v3.1 scoring system. In short, authentication is not well accounted for and confidentiality is insufficiently achieved by the implemented cryptographic measures. In consequence, an attacker who is nearby the bulb can operate at will not just the bulb but all devices of the Tapo family that the user may have on her Tapo account. Moreover, the attacker can learn the victim's Wi-Fi password, thereby escalating his malicious potential considerably. The paper terminates with an outline of possible fixes.

Attackers may attempt exploiting Internet of Things (IoT) devices to operate them unduly as well as to gather personal data of the legitimate device owners'. Vulnerability Assessment and Penetration Testing (VAPT) sessions help to verify the effectiveness of the adopted security measures. However, VAPT over IoT devices, namely VAPT targeted at IoT devices, is an open research challenge due to the variety of target technologies and to the creativity it may require. Therefore, this article aims at guiding penetration testers to conduct VAPT sessions over IoT devices by means of a new cyber Kill Chain (KC) termed PETIoT. Several practical applications of PETIoT confirm that it is general, while its main novelty lies in the combination of attack and defence steps. PETIoT is demonstrated on a relevant example, the best-selling IP camera on Amazon Italy, the TAPO C200 by TP-Link, assuming an attacker who sits on the same network as the device's in order to assess all the network interfaces of the device. Additional knowledge is generated in terms of three zero-day vulnerabilities found and practically exploited on the camera, one of these with High severity and the other two with Medium severity by the CVSS standard. These are camera Denial of Service (DoS), motion detection breach and video stream breach. The application of PETIoT culminates with the proof-of-concept of a home-made fix, based on an inexpensive Raspberry Pi 4 Model B device, for the last vulnerability. Ultimately, our responsible disclosure with the camera vendor led to the release of a firmware update that fixes all found vulnerabilities, confirming that PetIoT has valid impact in real-world scenarios.

We present Alexa versus Alexa (AvA), a novel attack that leverages audio files containing voice commands and audio reproduction methods in an offensive fashion, to gain control of Amazon Echo devices for a prolonged amount of time. AvA leverages the fact that Alexa running on an Echo device correctly interprets voice commands originated from audio files even when they are played by the device itself -- i.e., it leverages a command self-issue vulnerability. Hence, AvA removes the necessity of having a rogue speaker in proximity of the victim's Echo, a constraint that many attacks share. With AvA, an attacker can self-issue any permissible command to Echo, controlling it on behalf of the legitimate user. We have verified that, via AvA, attackers can control smart appliances within the household, buy unwanted items, tamper linked calendars and eavesdrop on the user. We also discovered two additional Echo vulnerabilities, which we call Full Volume and Break Tag Chain. The Full Volume increases the self-issue command recognition rate, by doubling it on average, hence allowing attackers to perform additional self-issue commands. Break Tag Chain increases the time a skill can run without user interaction, from eight seconds to more than one hour, hence enabling attackers to setup realistic social engineering scenarios. By exploiting these vulnerabilities, the adversary can self-issue commands that are correctly executed 99% of the times and can keep control of the device for a prolonged amount of time. We reported these vulnerabilities to Amazon via their vulnerability research program, who rated them with a Medium severity score. Finally, to assess limitations of AvA on a larger scale, we provide the results of a survey performed on a study group of 18 users, and we show that most of the limitations against AvA are hardly used in practice., Comment: 15 pages, 5 figures, published in Proceedings of the 2022 ACM Asia Conference on Computer and Communications Security (ASIA CCS '22)