Voice authentication (VA) has recently become an integral part in numerous security-critical operations, such as bank transactions and call center conversations.  The vulnerability of automatic speaker verification systems (ASVs) to spoofing attacks instigated the development of countermeasures (CMs), whose task is to differentiate between bonafide and spoofed speech.  Together, ASVs and CMs form today's VA systems and are being advertised as an impregnable access control mechanism.  We develop the first practical attack on spoofing countermeasures, and demonstrate how a malicious actor may efficiently craft audio samples against these defenses.  Previous adversarial attacks against VA have been mainly designed for the whitebox scenario, which assumes knowledge of the system's internals, or requires large query and time budgets to launch target-specific attacks. When attacking a security-critical system, these assumptions do not hold.  Our attack, on the other hand, targets common points of failure that all spoofing countermeasures share, making it real-time, model-agnostic, and completely blackbox without the need to interact with the target to craft the attack samples.  The key message from our work is that CMs mistakenly learn to distinguish between spoofed and bonafide audio based on cues that are easily identifiable and forgeable.  The effects of our attack are subtle enough to guarantee that these adversarial samples can still bypass the ASV as well and preserve their original textual contents.  These properties combined make for a powerful attack that can bypass security-critical VA in its strictest form, yielding success rates of up to 99\% with only 6 attempts.  Finally, we perform the first targeted, over-telephony-network attack on CMs, bypassing several known challenges and enabling a variety of potential threats, given the increased use of voice biometrics in call centers.  Our results call into question the security of modern VA systems and urge users to rethink their trust in them, in light of the real threat of attackers bypassing these measures to gain access to their most valuable resources.