Bibliographic record
Abstract
WPA3 (Wi-Fi Protected Access 3) is a certification that augments its predecessor WPA2 with protection mechanisms, such as resistance against password dictionary attacks through SAE (Simultaneous Authentication of Equals) handshake, MFP (Management Frame Protection) against management frame spoofing, and forward secrecy to prevent an attacker from decrypting old packets if it manages to crack the network key in the future. The mechanism is still under implementation by various device vendors. WPA3-capable devices are supposed to be on the market by the end of this year (2019) or early next year (2020). In this work, we describe a vulnerability that we have discovered in WPA3 authentication protocol. This vulnerability, named bad-token, can be exploited by an attacker in a race condition to cause a denial of service to Wi-Fi clients. The attacker sends fake authentication messages that contain a bad token (WPA3 authentication confirm value) during the WPA3 authentication and prevents legitimate clients from connecting to a WPA3 network. We also present two denial of service attacks related to WPA2, but can be inherited by WPA3. We start by presenting the WPA3-SAE mechanism and then introduce the bad-token vulnerability. We implement an attack that exploits the vulnerability using the Linux software utilities hostapd-2.7 and wpa_supplicant-2.7 on Raspberry Pis and show the impact of the attack on a legitimate WPA3 network. We provide a countermeasure to mitigate the attack. Finally, we present the two WPA2-related attacks that can occur on WPA3 if certain security measures are not applied. We experimentally show the feasibility of these two attacks and propose countermeasures to mitigate them and direct device vendors to better implement security in their future devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.068 | 0.040 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".